Robotics Lab Manual Final 545l

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EX NO: 01 DATE :

STUDY ON BASICS OF ROBOTS

Objective: To study the  Parts of the robot  Classification of robots

Description: The industrial robots shown in fig 1.1 resemble an inverted human arm mounted on a base. The most complex robotics system can be broken down into a few basic components. The various components of the robots are,

Fig 1.1: Industrial robotic arm

     

Manipulator End effector Actuator Sensors Power supply Means for programming

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Fig 1.1: Basic components of a robot

Manipulator: Manipulator is the main body of the robot and consists of the links, ts, and other structural elements of the robot. End Effector: End effector is the last part attached the last t of a manipulator which generally handles objects, makes connection to other machines or performs the required tasks. Grippers, welding torch, point spray gun, glue – laying gun etc. are some of the examples of end effector. Actuator: An actuator is a motor or valve that converts power in to robot movements. There are two basic types of actuators namely linear and rotary actuators. Linear actuators provide motion along a straight line. Rotary actuators provide rotation, moving their loads in arc or circle. Sensors: Sensors are used to collect information about the internal state of the robot or to communicate with the outside environment. Robots are often equipped with external sensory devices such as a vision system, touch and tactile sensors, speech synthesizers etc., which enables the robot to communicate with the outside world. Power Supply: Power supply provides the energy to drive the controller and actuators. It may convert ac voltage to the dc voltage require by the robots internal circuits, or it may be a pump or compressor providing hydraulic or pneumatic power. The three basic types or power supplies are electrical, hydraulic, and pneumatic.

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Means for programming: A robot may be programmed using any of several different methods. The teach pendant, also called a teach box or hand held programmer. The teach pendant, also called a teach box or hand held programmer shown in figure teaches a robot the movements required to perform a useful task. The operator uses a teach pedant to move the robot through the series of points that describes its desired path. Offline programming is one of the other methods where the programming is done on the computer using simulation software without actually connecting it to the robot. After the successful simulation in the software the robot can be loaded with the program.

Fig 1.1: Teach pendant

Classification of robot: Robot can be classified in two types based on their mobility.  Mobile Robots  Non Mobile Robots

Mobile Robots: Mobile Robots have the capability move from one place to another place in an environment. Usually a mobile robots will have wheels attached to a platform and in some cases such as in humanoid robot or other robot which resembles insect usually have legs for mobility. Other types of mobile robot are robots which has the ability to fly like quadricopter. Few examples of mobile robot are show in the below figure 1.2 and 1.3.

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Fig 1.2: ASIMO Humanoid robot developed by HONDA Fig 1.3: NASA ‘s SPIRIT ROVER in planet MARS

Non-mobile Robot: Industrial robotic arm is usually a non-mobile robot, which has a fixed base so it cannot move from one place to another. The robot shown in fig 1.4 is a typical industrial robot developed by KUKA.

Fig 1.4 is a typical industrial robot developed by KUKA.

Conclusion: By this above study experiment basic hardware components of robot and their classification based on their mobility has been studied successfully.

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EX NO: 02 DATE :

INTRODUCTION TO DEGREES OF FREEDOM AND CLASSIFICATION OF ROBOTS

Objective:  To study classification of robots based on workspace.  To study degrees of freedom of robots.  To study various robot ts. Description: Robots can be classified in various ways, depending on their components, configuration, and use. Three common methods of classifying robots are by the shape of the work envelope, types of control system used, , and the type of actuator drive used. Based on work envelope: Robots come in many sizes and shapes. The type of coordinate system used by the manipulator also varies. Work envelopes vary from one manufacturer to another, depending on the exact design of the manipulator arm. Combining different configurations in a single robot can result in another set of possible work envelopes. Before choosing a particular robot configuration, the application must be studied carefully to determine the precise work envelope requirements. Some work envelopes have a geometric shape; others are irregular. One method of classifying a robot is by the configuration of its work envelope. Some robots may be equipped for more than one configuration. The four major configurations are: Articulated, Cartesian, cylindrical, and spherical. Each configuration is used for specific applications.    

Cartesian – Three linear movement Cylindrical - two linear and one revolute t Spherical – one linear and two revolute t Articulated - all three revolute (human arm)

Cartesian Configuration: The arm movement of a robot using the Cartesian configuration can be described by three intersecting perpendicular straight lines, referred to as the X, Y, and Z axes .Because movement can start and stop simultaneously along all three axes, motion of the tool tip is smoother. This allows the robot to move directly to its designated point, instead of following trajectories parallel to each axis. The rectangular work envelope of a typical Cartesian configuration is illustrated in figure. One advantage of robots with a Cartesian configuration is that their totally linear movement allows for simpler controls. They also have a high degree of mechanical rigidity, accuracy, and repeatability. They can carry heavy loads, and this weight lifting capacity does not vary at different locations within the work envelope. As to disadvantages, Cartesian robots are generally limited in their movement to a small, rectangular work space. Typical applications for Cartesian robots include the following:  Assembly  Machining operations

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       

Adhesive application Surface finishing Inspection Water jet cutting Robotic X-ray and neutron radiography Automated CNC lathe loading and operation Remotely operated decontamination Advanced munitions handling.

Fig 2.1 Cartesian configuration

Cylindrical Configuration A cylindrical configuration consists of two orthogonal slides, placed at a 90° angle, mounted on a rotary axis. Reach is accomplished as the arm of the robot moves in and out. For vertical movement, the carriage moves up and down on a stationary post, or the post can move up and down in the base of the robot. Movement along the three axes traces points on a cylinder. A cylindrical configuration generally results in a larger work envelope than a Cartesian configuration. These robots are ideally suited for pick-and place operations. However, cylindrical configurations have some disadvantages. Their overall mechanical rigidity is reduced because robots with a rotary axis must overcome the inertia of the object when rotating. Their repeatability and accuracy is also reduced in the direction of rotary movement. The cylindrical configuration requires a more sophisticated control system than the Cartesian configuration.

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Typical applications for cylindrical configurations include the following:         

Machine loading and unloading Investment casting Conveyor pallet transfers Foundry and forging applications General material handling Meat packing Coating applications Assembly Injection molding

Fig 2.2 Cylindrical configuration

Spherical Configuration (Polar) The spherical configuration, sometimes referred to as the polar configuration, resembles the action of the turret on a military tank. A pivot point gives the robot its vertical movement, and a telescoping boom extends and retracts to provide reach. Rotary movement occurs around an axis perpendicular to the base. Fig illustrates the work envelope profile of a typical spherical configuration robot. The spherical configuration generally provides a larger work envelope than the Cartesian or cylindrical configurations.

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The design is simple and provides good weight lifting capabilities. This configuration is suited to applications where a small amount of vertical movement is adequate, such as loading and unloading a punch press. Its disadvantages include reduced mechanical rigidity and the need for a more sophisticated control system than either the Cartesian or cylindrical configurations. The same problems occur with inertia and accuracy in this configuration as they do in the cylindrical configuration. Vertical movement is limited, as well.

Fig 2.3 Spherical configuration Typical applications of spherical configurations include the following:        

Machine tool loading Heat treating Glass handling Parts cleaning Dip coating Press loading Material transfer Stacking and un stacking

Revolute Configuration (Articulated) The revolute configuration, or ted-arm, is the most common. These robots are often referred to as anthropomorphic because their movements closely resemble those of the human body. Rigid segments resemble the human forearm and upper arm. Various ts mimic the action of the wrist, elbow, and shoulder. A t called the sweep represents the waist. A revolute coordinate robot performs in an irregularly shaped work envelope. There are two basic revolute configurations: vertically articulated and horizontally articulated. The vertically articulated configuration has five revolute (rotary) ts.

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A vertically articulated robot is depicted. The ted-arm, vertically articulated robot is useful for painting applications because of the long reach this configuration allows. The horizontally articulated configuration generally has one vertical (linear) and two revolute ts. Also called the SCARA (selective compliance assembly robot arm) configuration, it was designed by Professor Makino of Yamanashi University, Japan. The primary objective was a configuration that would be fairly yielding in horizontal motions and rather rigid in vertical motions. The basic SCARA configuration, is an adaptation of the cylindrical configuration. The SCARA robot is designed for clean-room applications, such as wafer and disk handling in the electronics industry. SCARA robots are ideally suited for operations in which the vertical motion requirements are small compared to the horizontal motion requirements. Such an application would be assembly work where parts are picked up from a parts holder and moved along a nearly horizontal path to the unit being assembled. The revolute configuration has several advantages. It is, by far, the most versatile configuration and provides a larger work envelope than the Cartesian, cylindrical, or spherical configurations. It also offers a more flexible reach than the other configurations, making it ideally suited to welding and spray painting operations. However, there are also disadvantages to the revolute configuration. It requires a very sophisticated controller, and programming is more complex than for the other three configurations. Different locations in the work envelope. can affect accuracy, load-carrying capacity, dynamics, and the robot’s ability to repeat a movement accurately. This configuration also becomes less stable as the arm approaches its maximum reach. Typical applications of revolute configurations include the following:            

Automatic assembly Parts and material handling In-process inspection Palletizing Machine loading and unloading Machine vision Material cutting Material removal Thermal coating Paint and adhesive application Welding Die casting

Degrees of Freedom Although robots have a certain amount of dexterity, it does not compare to human dexterity. The movements of the human hand are controlled by 35 muscles. Fifteen of these muscles are located in the forearm. The arrangement of muscles in the hand provides great strength to the fingers and thumb for grasping objects. Each finger can act alone or together with the thumb. This enables the hand to do many intricate and delicate tasks. In addition, the human hand has 27 bones. Figure shows the bones found in the hand and wrist. This bone, t, and muscle arrangement gives the hand its dexterity. Degrees of freedom (DOF) are a term used to describe a robot’s freedom of motion in three-dimensional space—

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specifically, the ability to move forward and backward, up and down, and to the left and to the right. For each degree of freedom, a t is required. A robot requires six degrees of freedom to be completely versatile. Its movements are clumsier than those of a human hand, which has 22 degrees of freedom. The number of degrees of freedom defines the robot’s configuration. For example, many simple applications require movement along three axes: X, Y, and Z. These tasks require three ts, or three degrees of freedom. The three degrees of freedom in the robot arm are the rotational traverse, the radial traverse, and the vertical traverse. The rotational traverse is movement on a vertical axis. This is the side-to-side swivel of the robot’s arm on its base. The radial traverse is the extension and retraction of the arm, creating in-and-out motion relative to the base. The vertical traverse provides up-and-down motion. For applications that require more freedom, additional degrees can be obtained from the wrist, which gives the end effecter its flexibility. The three degrees of freedom in the wrist have aeronautical names: pitch, yaw, and roll. The pitch, or bend, is the up-and-down movement of the wrist. The yaw is the side-to-side movement, and the roll, or swivel, involves rotation. A robot requires a total of six degrees of freedom to locate and orient its hand at any point in its work envelope. Although six degrees of freedom are required for maximum flexibility, most applications require only three to five. When more degrees of freedom are required, the robot’s motions and controller design become more complex. Some industrial robots have seven or eight degrees of freedom. These additional degrees are achieved by mounting the robot on a track or moving base.

Fig 2.4 t and links of human arm

Fig 2.5 Degrees of freedom

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Robot ts

Fig 2.6 t type The ts in robots are categorized into two types. They are,  linear and  rotary Linear ts provide motion along a straight line; they extend or retract their attached loads. Rotary ts provide rotation, moving their loads in an arc or circle. Rotary motion can be converted into linear motion using a lead screw or other mechanical means of conversion. These types of actuators are also used outside the robot to move work pieces and provide other kinds of motion within the work envelope.

Conclusion: Thus the classification of robots based on work space, degrees of freedom of robots and Robot ts were studied.

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EX NO: 03 DATE :

STUDY ON KINEMATICS OF ROBOTIC ARM

Objective: To study the  Forward kinematics of Robots  Inverse kinematics of robots

Description: Forward Kinematics of Robots Forward kinematics is the method for determining the orientation and position of the end effector, given the t angles and link length of the robotic arm. For forward kinematics, we will have to develop a set of equations that relate to the particular configuration of a robot such that by substituting the t and link variables in these equations, the position and orientation of the robot can be calculated. A robot manipulator is composed of a set of links connected together by various ts. The ts can either be very simple, such as revolute ts or prismatic ts. Cartesian coordinates There will be a three linear movements along the three major x,y,z axes. In this type of a robot, all actuators are linear, and the positioning of the hand of the robot is accomplished by moving the three linear ts along the three axes. A gantry robot is basically a Cartesian coordinate robot, except that the robot is usually attached to a rectangular frame upside down.

é ê ê T =ê ê êë

1 0 0 Px ù ú 0 1 0 Py ú ú 0 0 1 Pz ú 0 0 0 1 úû

Fig 3.1 Cartesian configuration and transformation matrix Of course, since there are no rotations, the transformation matrix representation this motion to point p is a simple translation transformation matrix, as shown next. Please note that here we are only referring to the position of the origin of the frame, and not its orientation. The transformation matrix representing the forward kinematic equation of the position of the hand of the robot in a Cartesian coordinates system will be by the three transformations that relates the origin of the hand frame can be found by pre multiplying by each matrix as follows

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Cylindrical coordinates:

n

o a

Z

P

Y 𝛼 X

Fig 3.2 Cylindrical coordinates

é ê T =ê ê ê ë

1 0 0 0

0 1 0 0

0 0 ùé Ca -Sa úê 0 0 úê Sa Ca 1 l úê 0 0 ú ê 0 1 ûë 0 0 é ê T =ê ê ê ë

Ca -Sa Sa Ca 0 0 0 0

0 0 1 0

0 0 0 1

ùé úê úê úê úê ûë

0 rCa 0 rSa 1 l 0 1

1 0 0 0

0 1 0 0

0 0 1 0

r 0 0 1

ù ú ú ú ú û

ù ú ú ú ú û

A Cylindrical coordinate system includes two linear translations and one rotation. The sequence is a translation of r along the axis, a rotation of α about the z axis, and a translation of l along the z axis, as shown in fig. Since these transformation are all relative to the axes of the universe reference frame, the total transformation caused The first three columns represent the orientation of the frame after this series of transformations. However, at this point, we are only interested in the position of the origin of the frame, or the last column. Obviously, in cylindrical coordinate movements, due to the rotation α about the z axis, the orientation of the moving frame will change. This orientation change will be discussed later. Spherical coordinates. Spherical coordinate system consists of one linear motion and two rotations. The sequence is a translation of r along the z axis, a rotation of β about the y axis, and a rotation of γ about the z axis as shown in fig. Since these transformation are all relative to the axes of the universe reference frame, the total transformation caused by the three transformations that relates the origin of the hand frame can be found by pre multiplying by each matrix as follows

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é ê T =ê ê ê êë

Cg

-Sg

Sg

Cg

0 0

0 0

0 0 ùé Cb úê 0 0 úê 0 1 l úúêê -Sb 0 1 úûêë 0

é Cb.Cg ê ê Cb.Sg T =ê 0 ê êë 0

Sb

0

1 0 0 Cb 0

0

-Sg

Sb.Cg

Cg

Sb.Sg

0

Cb

0

0

0 ùé 1 úê 0 úê 0 0 úê 0 úê 1 ûúë 0

0 1 0 0

0 0 1 0

0 0 r 1

ù ú ú ú ú û

rSb.Cg ù ú rSb.Sg ú rCb úú úû 1

The first three columns represent the orientation of the frame after this series of transformations. While the last column is the position of the origin. Articulated coordinates. Articulated coordinates consist of three rotations. Forward kinematic equation for articulated arm can be represented by using DENAVIT – HARTENBERG representation. Fig: 3.3 DENAVIT – HARTENBERG

Z(i - 1) Y(i -1) X(i -1)

un( i

Yi a(i - 1 )

di

Zi Xi

ai Ui

- 1)

Each t is assigned a coordinate frame. Using the Denavit-Hartenberg notation, you need 4 parameters to describe how a frame (i) relates to a previous frame ( i -1 ). 1) a(i-1) Technical Definition: a(i-1) is the length of the perpendicular between the t axes. The t axes is the axes around which revolution takes place which are the Z (i-1) and Z(i) axes. These two axes can be viewed as

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lines in space. The common perpendicular is the shortest line between the two axis-lines and is perpendicular to both axis-lines. Visual Approach - “A way to visualize the link parameter a(i-1) is to imagine an expanding cylinder whose axis is the Z(i-1) axis - when the cylinder just touches the t axis i the radius of the cylinder is equal to a(i1).” (Manipulator Kinematics) It’s Usually on the Diagram Approach - If the diagram already specifies the various coordinate frames, then the common perpendicular is usually the X(i-1) axis. So a(i-1) is just the displacement along the X(i-1) to move from the (i-1) frame to the i frame. If the link is prismatic, then a(i-1) is a variable, not a parameter. 2) a(i-1) Technical Definition: Amount of rotation around the common perpendicular so that the t axes are parallel.i.e. How much you have to rotate around the X(i-1) axis so that the Z(i-1) is pointing in the same direction as the Zi axis. Positive rotation follows the right hand rule. 3) d(i-1) Technical Definition: The displacement along the Zi axis needed to align the a(i-1) common perpendicular to the ai common perpendicular. In other words, displacement along the Zi to align the X(i-1) and Xi axes. 4) Ui Amount of rotation around the Zi axis needed to align the X(i-1) axis with the Xi axis. The Denavit-Hartenberg Matrix

 sinθi 0 a(i 1)   cosθi sinθ cosα  cosθ cosα  sinα  sinα d i (i  1) i (i  1) (i  1) (i  1) i   sinθisinα(i 1) cosθisinα(i 1) cosα(i 1) cosα(i 1)di    0 0 0 1  

Conclusion: Thus the forward and inverse kinematics of robotic arm has been studied successfully .

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EX NO: 04 DATE :

STUDY ON MOBILE ROBOTS

Objective: To study the  Applications of the robots  Mechanics of the robots

Description: Robot: Robot is a reprogrammable multi functional manipulator; Which Follows programmed paths to fulfill a large variety of tasks. For example, material handling. Classification: Basically robots are classified into two types based on their behavior. They are mobile and non mobile robots. Mobile robots: These mobile robots will be having a Platform with a large mobility within its environment (air, land, underwater) with the following functional characteristics:  Mobility: total mobility relative to the environment  A certain level of autonomy: limited human interaction  Perception ability: sensing and reacting in the environment The robots have potential application in areas where a vehicle or a mechanic automatic system may exist. Applications of Mobile Robots :  MEDICAL SERVICES as Service Robots o Transportation of food, medication, medical exams, o Automation of pharmacy service  AUTOMATIC CLEANING of (large) areas o Supermarkets, airports, industrial sites o Glass cleaning o Domestic vacuum-cleaner  CLIENT o Museum tours, exhibitions guides  AGRICULTURAL o Fruit and vegetable picking, fertilization, planting

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 FORESTS o Cleaning, fire preventing, tree cutting  HAZARD ENVIRONMENTS o Inspection of hazard environments (catastrophic areas, volcanoes, nuclear power plants, oil tanks) o Inspection of gas or oil pipes, and power transmission lines o Oil tank cleaning  SPACE o Space exploration o Remote inspection of space stations  MILITARY o Surveillance vehicles o Monitoring vehicles  MATERIAL HANDLING o AGVs, SGVs, LGVs  ENTERTAINMENT o Robot Dog o Aibo – Robot dog from Sony o Tele presence Components of a Mobile Robot A mobile robot is a combination of various physical (hardware) and computational (software) components. In of hardware components, a mobile robot can be considered as a collection of subsystems for:    

Locomotion (how the robot moves through its environment) Sensing (how the robot measures properties of itself and its environment) Reasoning (how the robot maps the measurements into actions) Communication how the robot communicates with an outside Operator)

In of software components, sets of subsystems are responsible for:  Planning (To plan its various aspect)

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YouBot Hardware Descriptions And Kinematics Youbot is basically a mobile platform with a 5 axes serial kinematic arm and two-finger gripper. It is an open platform, which means it can be controlled using open source simulation software such as VREP, OpenRAVE, Webots [7]. The hardware and kinematics has been described in two separate parts, arm manipulator and mobile platform to get better understanding since algorithm for path plan has been developed separately based on their hardware and kinematics. Mecanum Wheels In general there are two types of wheels, conventional wheel with a steering system and other is an omnidirectional wheel. Youbot is an omnidirectional platform with Mecanum wheel, which can be driven in any direction without any requirement of steering wheel.

Fig 1 -Mobile Platform (source – KUKA Youbot Store) As shown in Fig 1 each wheel has six rollers arranged on the surface of the wheels. The angle between the roller and the center of the wheel axis is arranged at 45 . When the wheel rotates part of the force is in the direction of rotation and other part is normal to directional of the wheel. This makes the wheel to move in any direction with minimum friction hence the platform have 3 degrees of freedom. The wheel motion can be divided into ive and active direction. Active direction is the axis in which the roller is in with the ground and ive is perpendicular to roller axis. Kinematics Of Omni Directional Platform Fig 2 shows that mobile platform has four mecanum wheels, which are arranged at four corners of the rectangular platform. The platform has been developed with following movements namely (forward, backward, left, right) translational movement and rotational movement. represents the velocity in x-axis represents the velocity in y-axis Wz signifies the angular velocity and represents distance between the wheel axis and the center of Youbot in x and y axis respectively.

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Fig 2-Kinematics of Mobile Platform The traversing direction of the platform can be determined using a force vector that is calculated by the resulting combination of part of the force along the direction of rotation of each wheel and the force perpendicular to the direction of the each wheel rotation. Kinematics can be explained using the forward kinematics and inverse kinematics equation as given below. Forward Kinematics In forward kinematics, the resultant velocity of the platform can be calculated if the velocity of each wheel is known. The equation (2) for calculating the forward kinematics is give below.

1

Vx Vy

=

1

1

𝜔1

1

𝜔2

R/4 1

Wz

-1

-1

1

𝜔3 𝜔

Where, R is the radius of the wheel, K = l1 +l2 Inverse Kinematics In inverse kinematics, the velocity of the platform is known and so velocity for each wheel has to be calculated. This is done by inverse kinematics equation (2) 𝜔1 𝜔2 𝜔3 𝜔

1

1

1

1

= 1/ R

Vx Vy

1

-1

-1

1

Wz

20

Where, R is the radius of wheel, K = l1 +l2 Motion Dynamics Below tables describes the different motion dynamics of Youbot mobile platform.

Direction

45

Front Right Wheel Clockwise Clockwise Zero Anticlockwise Anticlockwise Zero Anticlockwise Anticlockwise Zero Clockwise Clockwise Zero Zero

Front Left Wheel Clockwise Clockwise Zero Anticlockwise Anticlockwise Zero Clockwise Zero Clockwise Anticlockwise Zero Anticlockwise Clockwise

Rear Right Wheel Clockwise Zero Clockwise Anticlockwise Zero Anticlockwise Anticlockwise Zero Anticlockwise Clockwise Zero Clockwise Zero

Rear Left Wheel Clockwise Zero Clockwise Anticlockwise Zero Anticlockwise Clockwise Clockwise Zero Anticlockwise Anticlockwise Zero Clockwise

315

Zero

Anticlockwise

Zero

Anticlockwise

135

Clockwise

Zero

Clockwise

Zero

225

Anticlockwise

Zero

Anticlockwise

Zero

90

270

0

180

Table shows different combination of wheel rotation results in a motion of mobile platform in different direction. By the Table it is clear that four, three and two wheel rotation is possible. Due to the presence of rollers in the wheels it is not necessary that always four wheels have to be rotated in order to move in a particular direction. Wheel velocities can be calculated by using inverse kinematics equation as explained earlier. This will be later used in the motion planning of the mobile platform.

Conclusion: By this above study experiment applications of robots and mechanics of mobile robot (Kuka Youbot) has been studied successfully.

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EX NO: 05 DATE :

STUDY ON VREP SOFTWARE PACKAGE

Objective: To study the  VREP software package  Programming tool interface

Description: VREP Simulation Environment The software used to simulate the path planning of Youbot is VREP (Virtual Robot Experimentation Platform), version 3.0.4. It has a 3 dimensional simulation environment, which can be interfaced with various programming tools such as C++, Matlab, JAVA, Lua script, Urbi and Python. Interface

Toolbar Model browser Scene hierarchy

Menu bar

Scene

Toolbar

Fig 1 – VREP Interface Fig 1 shows interface of VREP simulation tool and has six components, which are toolbar, model browser, scene, menu bar and scene hierarchy. Toolbar has all the functional part necessary to run the simulation and change simulation settings based on requirements. Model browser displays the list of all the default models available in the simulation tool. A scene acts as a 3 dimensional space where single or several models can be placed and scene hierarchy displays the list of models and their object present in the current scene.

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Fig 2 – Scene Object types (source - VREP tutorial)

Model And Scene Objects A model is a sub element of a scene and each model has collection of objects. A model acts as single entity. One of the objects of the model is flagged as base object to which all the other objects are attached. The base object is the parent and the other entire object in the base is a child. Selecting one of the objects under this base object selects the entire model as single entity.Each model can have several object types as shown in Fig 2. The object types whose properties are modified in this thesis are shape, t, dummy, and graph. A shape is a geometrical structure of an object. A t is an actuator, which is used for mobility or to do some task which involves movement. There are several ts such as revolute t, prismatic t and spherical ts. Revolute t reflects the motor in simulation and prismatic t for sliding movement such as gripper. Dummy is an important object type, which is simply a point in space with a co-ordinate frame of its own, attached to it. These dummies are very important for moving the arm to a goal position or to move a robot towards a goal position. A graph is used to generate 2d or 3d graph while the simulation is running whose properties can be modified to suit the needs of our requirement. Scene Objects Properties Each scene object has certain properties based on the object type and the properties can be modified using scene object property dialog as shown in Fig 3. This dialog mainly has two divisions, which are common and object specific property. Object specific properties are based on the object types for e.g. if the object type is shape then it has shape as specific property, if the object type is t then it has t as specific property in which t mode and t dynamic parameter can be modified.

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Fig 3 – VREP Scene object property dialog

Fig 4 – VREP Scene object/item/position/orientation dialog The common property is the general property of the object, which shows whether it is selectable or not, visibility etc. The common property part also has some special property option such as whether the object is collidable, measurable, cuttable, detectable etc. The important property that is modified in this thesis is t mode. t mode has several options such as force or torque mode, inverse kinematic mode, ive mode, motion dependent mode, and motion independent mode. In force or torque mode a t position control is disabled and only velocity can be controlled. In inverse kinematic mode the t can modified by using the inverse kinematic calculation module, which will be, described later. The other properties, which can be changed, are position and orientation of an object using object/item position/orientation dialog as shown in Fig 4.

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Calculation Modules VREP has calculation modules as shown in Fig 5 which are default algorithm embedded in the simulation tool for path planning, distance calculation, inverse kinematics, motion planning, dynamics and collision detection. The module, which used in this thesis is inverse kinematics module for calculating the t values if the gripper position is known.

Fig 5 – VREP Calculation Modules Programming Tool Interface VREP communicates with programming tool using application programing interface or commonly known as API. VREP s regular API AND remote API.VREP has embedded programming tool which s Lua scripting language. Regular API represents the communication of application engine with embedded script of the VREP. Remote API s communication between VREP and external programming tool or hardware. In this thesis VREP is interfaced with MATLAB as remote API client –server connection. VREP acts as a server and MATLAB program as a client. VREP has embedded main script, which handles all the communication and execution of the child script. Child script is an embedded script associated with the scene objects and there can be several child script in the model. VREP calls client through the child script associated with base object. The client application can also communicate with child script by sending string or integer signal. By this, the control can also be coordinated between embedded child script and the client script. Finally Matlab ends communication by calling a remote API function, which terminates the communication between client and server. Conclusion: By this above study experiment VREP software package and there programming tool interface has been studied successfully.

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EX NO: 06 DATE :

STUDY ON PROGRAMMING OF ROBOTS

Objective: To study the  Programming in MATLAB  Programming in LUA script Description: VREP and Matlab are connected as server-client interface. Matlab act as client application, which communicates with VREP via socket communication. Initially the client should be successfully connected to the server for the execution of program in Matlab. VREP on the server side is initiated using the following function -1 in Lua Script associated with base object. SimExtRemoteApiStart (portAddress)

Remote API Function – 1

Client Main Function The main function is the main client function, which establish communication with server application for the entirety of the simulation run. All the other function in Matlab is called from this function. The client side starts the communication by following function -2. [client ID]=simxStart(Address,connectionPort,booleanwait,booleanReconnect,timeOut,ThreadCycle)

Remote API Function – 2

Matlab is connected to VREP using remote API functions. The function, which call server, is the main function under which all the subsequent function are added to it. Once communication has been established any commands can be given from Matlab to VREP to control Youbot. If the communication is lost for some reason the simulation software execute last sent command. There are some Remote API functions to overcome the error and to properly terminate communication. All remote API functions have error codes and these codes are integers. Based on this integer the interface problem can be identified and can be rectified easily. Client Main Function The main function is the main client function, which establish communication with server application for the entirety of the simulation run. All the other function in Matlab is called from this function. The client side starts the communication by following function -2. Address is a string name and connection port is a port number to connect. If Boolean Reconnect is true then it means if once communication with VREP has been terminated it will not try to reconnect. Time out is maximum time limit in milliseconds for trying to establish a communication. Thread cycle is the frequency of data packets sent and received between VREP and Matlab. Once the simulation run has finished, client should end communication by calling the following function-3.

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SimxFinish (client ID)

Remote API Function – 3 Basic Control Functions The client Matlab program has declaration stage in which all the object handles has to be obtained in separate variables in order to send control commands to a specific object. For example to send a velocity value to a wheel the wheel handle should be first obtained. [ErrorCode, number handle]=simxGetObjectHandle(clientID,objectName,operationMode)

Remote API Function – 4 Function-4 shown above is to obtain handles of the object.

Specific operation modes are required for each remote API function. Simx_opmode_oneshot_wait

Operation mode – 1

Operation mode – 1 is a blocking mode, which sends request to server and waits for the actual server reply. If the reply is not obtained then an error code is generated after specified time. There is one other mode which is used less frequently is Simx_opmode_oneshot

Operation mode – 2

Operation mode – 2 is a non-blocking mode, which does not wait for the actual reply from the server but sends back previous replies. Once object handles has been retrieved all necessary data with respect to the particular object can be obtained and control commands can be sent to modify the object. The position values for an object can be obtained by Function -5 [ErrorCode,array]=simxGetObjectPosition(clientID,objectHandle,relativeObjectHandle,operationMode)

Remote API Function – 5

Velocity of an object can be set by Function -6 [ErrorCode]=simxSettTargetVelocity(clientID,tHandle,targetVelocity,operationMode)

Remote API Function – 6

Target velocity is a one-dimensional value. Velocity can be either angular velocity value or linear velocity depending on the t type. [ErrorCode,array]=simxGetObjectPosition(clientID,objectHandle,relativeObjectHandle,operationMode)

Remote API Function – 7

The gripper target dummy position is obtained by calling Function -7. Then the target dummy can be given a new position by using the Function-8.

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[ErrorCode]=simxSetObjectPosition(clientID,objectHandle,relativeObjectHandle,position,operationMode)

Remote API Function – 8

It sets an object position, which is a array of position value in each axis. Based on the new position value of the gripper target dummy the IK module computes inverse kinematics calculations and respective t values are set for each ts and then gripper tip dummy follows the target dummy. Similarly orientation can also be obtained. Gripper Control The primary goal is to grab or drop the object after reaching the goal position. There are several ways to implement gripper control either directly from client or by sending signal from client to child script of the gripper. The child script continuously checks for the signal, if the signal is sent then it unpacks the data packets. The data packet sent is a Boolean variable. If it is true then gripper ts closes until it touches an object. By default the gripper t always stays open until a string signal is sent. packed Data=simxPackInts(array integer values)

Remote API Function – 9

The Function 9 packs the array of integer values. [ErrorCode]=simxAppendStringSignal(clientID,signalname,arrayinteger value,operationMode)

Remote API Function – 10

Function 10 sends the packed value under signal name and it is sent to the child script in VREP simulation environment. The child script closes or opens the gripper based on the value sent. PROGRAMMING IN LUA SCRIPT BASIC COMMANDS GET OBJECT HANDLE Syntax number objectHandle=simGetObjectHandle Description Retrieves an object handle based on its name. GET OBJECT POSITION Syntax table_3 position=simGetObjectPosition Description Retrieves the position of an object.

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SET OBJECT POSITION Syntax number result=simSetObjectPosition Description Sets the position (x, y and z-coordinates) of an object. Dynamically simulated objects will implicitely be reset before the command is applied. SET TRAJECTORY VELOCITY Syntax number result=simSettTargetVelocity Description Sets the intrinsic target velocity of a non-spherical t. This command makes only sense when the t mode is: (a) motion mode: the t's motion handling feature must be enabled, (b) torque/force mode: the dynamics functionality and the t motor have to be enabled. GET TRAJECTORY VELOCITY Syntax number targetVelocity=simGettTargetVelocity Description Retrieves the intrinsic target velocity of a non-spherical t. HANDLE IK GROUP Syntax number calculationCountOrResult=simHandleIkGroup Description Handles (solves) a ed IK group. IK groups can be ed while editing a scene.

Conclusion: By this above study experiment programming of a robot in VREP using LUA script and MATLAB has been studied successfully.

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EX NO: 07 DATE :

MOTION PLANNING OF MOBILE ROBOT (KUKA YOUBOT)

Objective: The objective of this exercise is to write a program to move the Youbot from its start position to goal position using the Lua script in VREP simulation software. Description:  Open a new scene from the file menu of VREP simulation software.  From the model browser open folder named mobile.  Drag down the model browser and pick up the KUKA YOUBOT and place it in the simulation environment.  Now select the child script of YOUBOT and delete all the program codes  Define the goal point by creating a dummy and placing it in the specific location (reference frame).  Now develop your own algorithm to move the Youbot from start to goal position  Calculate the shortest distance from the start to goal point by the distance formula.  Now define your own logic to give velocity to each wheel and make the robot to stop near the goal.

Pseudo code if (simGetScriptExecutionCount()==0) then Get all necessary objects handle simHandleChildScript(sim_handle_all_except_explicit) Define start and goal point Calculate shortest distance Give velocity for each wheel Stop the robot at goal end

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Fig 7- Model motion of Youbot to reach goal position

Result: Thus successful simulation of movement of Youbot from a specific start point to a goal point has completed

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EX NO: 8 DATE :

Motion planning of Robotic Arm in circular path

Objective: The objective of this exercise is to write a program to make the Youbarm to follow a circular path.

Description:

     

Open a new scene from the file menu of VREP simulation software. From the model browser open folder named mobile. Drag down the model browser and pick up the KUKA YOUBOT and place it in the simulation environment. Now select the child script of YOUBOT and delete all the program codes Define at least 10 points by creating a dummy and placing it in the specific location to form a circular (reference frame). Now develop your own algorithm to make the Youbot arm to follow the predefined path.

Pseudo code if (simGetScriptExecutionCount()==0) then Get all necessary objects handle simHandleChildScript(sim_handle_all_except_explicit) Define the set of points to be followed Set target position points to gripper Call inverse Kinematics algorithm Give incremental position to the gripper Stop the gripper at the goal End

Result: Thus successful simulation of movement of Youbot arm to follow a specific path has been successfully done

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EX NO: 9 DATE :

Motion planning of Robotic Arm in straight line path

Objective: The objective of this exercise is to write a program to move the Youbot arm from its start position to goal position such that it follows a straight-line trajectory using the Lua script and create successful simulation in VREP simulation software.

Description:

       

Open a new scene from the file menu of VREP simulation software. From the model browser open folder named mobile. Drag down the model browser and pick up the KUKA YOUBOT and place it in the simulation environment. Now select the child script of YOUBOT and delete all the program codes Define the goal point by creating a dummy and placing it in the specific location (reference frame). Now develop your own algorithm to move the Youbot arm from start to goal position Calculate the shortest distance from the start to goal point by the distance formula. Now define your own logic to give velocity to each wheel and make the robot to stop near the goal.

Pseudo code if (simGetScriptExecutionCount()==0) then Get all necessary objects handle simHandleChildScript(sim_handle_all_except_explicit) Define start and goal point for the arm Calculate shortest distance Call inverse Kinematics algorithm Give incremental position to the gripper Stop the gripper at the goal End

Result: Thus successful simulation of movement of Youbot arm from a specific start point to a goal point has completed.

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EX NO: 10 DATE :

PICK AND PLACE OPERATION BY ROBOTIC ARM

Objective: The objective of this exercise is to write a program to up pick an object from the floor and place the object in same position using the Lua script in VREP simulation software.

Description:  Open a new scene from the file menu of VREP simulation software.  From the model browser open folder named mobile.  Drag down the model browser and pick up the KUKA YOUBOT and place it in the simulation environment.  Now right click on the mouse and select add primitive shape.  In primitive shape select cuboid and a window will open.  Now select pure shape in the window and create a cuboid of dimension 0.04  Now add a dummy similar to the steps for creating cuboid and place it in the center of the cuboid  Now make the dummy a child of the cuboid by right clicking the dummy and cuboid and selecting the option “last selected object a parent”.  Select the cuboid and now select object/item shift from menubar, give position values such that cuboid is placed in the platform of the YOUBOT.  Now select the child script of YOUBOT and delete all the program codes  Type the following command “if (simGetScriptExecutionCount()==0) then” in child script of Youbot  Now develop your own algorithm to pick up the object from the location and place it on the same location using the Lua script functions.

Fig: 8.1 Model movement of the arm

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Pseudo code if (simGetScriptExecutionCount()==0) then Get all necessary objects handle simHandleChildScript(sim_handle_all_except_explicit) Define start and goal point Calculate intermediate points for the arm to follow Set the arm to follow the points.

Result: Thus successful simulation of picking up an object and placing back in its own position using Lua script programming tool has been done.

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EX NO: 11 DATE :

PICK AND PLACE OPERATION BY ROBOTIC ARM USING MATLAB

Objective: The objective of this exercise is to write a program to up pick an object from the floor and place the object in same position using the MATLAB and interfacing it with VREP simulation software.

Description:  Open a new scene from the file menu of VREP simulation software.  From the model browser open folder named mobile.  Drag down the model browser and pick up the KUKA YOUBOT and place it in the simulation environment.  Now right click on the mouse and select add primitive shape.  In primitive shape select cuboid and a window will open.  Now select pure shape in the window and create a cuboid of dimension 0.04  Now add a dummy similar to the steps for creating cuboid and place it in the center of the cuboid  Now make the dummy a child of the cuboid by right clicking the dummy and cuboid and selecting the option “last selected object a parent”.  Select the cuboid and now select object/item shift from menubar, give position values such that cuboid is placed in the platform of the YOUBOT.  Now select the child script of YOUBOT and delete all the program codes  Type the following command “simExtRemoteApiStart(Portaddress)” in child script of Youbot.  Now develop your own algorithm to pick up the object from the location and place it on the same location using the Matlab functions.

Fig: 9.1 Model movement of the arm

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Pseudo code vrep=remApi('remoteApi','extApi.h'); (Call the library) clientID=vrep.simxStart('127.0.0.1',8080,true,true,5000,5); (Initializing communication with VREP) if (clientID>-1) Get all necessary objects handle Define start and goal point Calculate intermediate points for the arm to follow Set the arm to follow the points. vrep.simxFinish(clientID); vrep.delete();

Result: Thus successful simulation of picking up an object and placing back in its own position using Matlab programming tool has been done.

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EX NO: 12 DATE :

MOTION PLANNING OF MOBILE PLATFORM (KUKA YOUBOT) USING MATLAB

Objective: The objective of this exercise is to write a program to move the Youbot from its start position to goal position using the Matlab in VREP simulation software. Description:  Open a new scene from the file menu of VREP simulation software.  From the model browser open folder named mobile.  Drag down the model browser and pick up the KUKA YOUBOT and place it in the simulation environment.  Now select the child script of YOUBOT and delete all the program codes  Define the goal point by creating a dummy and placing it in the specific location (reference frame).  Type the following command “simExtRemoteApiStart(Portaddress)” in child script of Youbot.  Now develop your own algorithm in MATLAB to move the Youbot from start to goal position  Calculate the shortest distance from the start to goal point by the distance formula.  Now define your own logic to give velocity to each wheel and make the robot to stop near the goal.

Pseudo code if (simGetScriptExecutionCount()==0) then Get all necessary objects handle simHandleChildScript(sim_handle_all_except_explicit) Define start and goal point Calculate shortest distance Give velocity for each wheel Stop the robot at goal end

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Fig 10.1- Model motion of Youbot to reach goal position

Result: Thus successful simulation of movement of Youbot from a specific start point to a goal point has completed.

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