Indispensable Self-Governing Turtlebot Project - Coursework Example

TurtleBot Name Course Tutor Date: October 27, 2012 Outline Abstract Introduction Task statement Task analysis Description of the solution Experiment results Discussion of difficulties encountered Summary of solution Conclusion Future direction Abstract The aim of the paper was to programme a robot to be able to avoid obstacles while accessing interior part of the basement of a building to dedonate a bomb that is in the building. The robot was assumed to use sensors to avoid hindrances and walk within distances that were predetermined. TurtleBot will be used to carry out dangerous tasks to human beings. To able to carry this task TurtleBot has sensors and controller that have been applied. Its movement is guided with guidance, sensors and remote control from the operator. From the signal of the operator the robot makes forward movement thus making robot to move forward as well as turning in same time. We have written the programme in a manner that the behavior of the robot is able to make motions which indicate that it’s moving in a certain path without deviating. The movements of the robot used equilibrium point control that was installed in it and upon reaching a required area safe. The surroundings of the robot will have some obstacles which the robot was expected to avoid while trying to remove the debris that represented a bomb. The velocity of the robot was controlled to make sure that there was no collision with the wall or other obstacles while moving towards the debris. Introduction The project taken up intends to design a robot which can be used by humans to reach areas which can not be reached by human beings or if human beings happens to reach the place. The purpose of the paper is to programme a robot to be able to carry out tasks of making movements, taking a red color cloth from debris, make a sound after performing some actions, carrying up the debris and transporting it back to the original point. In programming the robot, Robot operating system was used to have codes that will show the actions taken by the robot. The software will provide codes that are supposed to be used in ensuring proper behaviors are taken by the robots to avoid obstacles or mis-ups that may cause destruction. The robot is required to use some camera to identify the areas where the debris is placed as well as the red cloth. The ground where the robot will walk will be flat except the stairs which will be designed in a manner that will enable the robot walk into a basement of building in future. The robot will be designed in a manner that will take a shorter time to capture the images of the debris and identify where the cloth is placed. This is a multi-task activity because, the robot will not only required to carry out one activity but many. TurtleBot can effectively navigate unknown territory pick up something without failure. TurtleBot is given a starting location; it must be able to move forward throughout its environment without having knowledge of a predetermined path. TurtleBot is designed for ground on certain path using designed under several frameworks which include: knowledge-based systems, real time planning, world modeling, value-driven reasoning as well as intelligent communication. In addition to making decisions, these robots must be able to explore, predict, communicate as well as escape. However, incorporating programming into the robot controls will optimize the activities of the robot with minimal or no human interference. Programming will allow autonomous robots to select certain paths and make decisions that will optimize outcomes. In addition, more attention is also being placed on designing autonomous robots so that they are able to effectively interact with one another without disrupting work flows and processes. Programming a TurtleBot will make it possible to perform tasks effectively; the robots are required to avoid obstacles, cover the terrain effectively and carry the workload. Task statement The robot will be required to find debris situated in a certain corner of a building. This means the robot will carry out various tasks like making movement finding debris taking it up and walking to the same position it was. The root will be required to make a sound once it finds the debris. When it picks it up it is required to sing happy birthday song. This means the robot will be required to navigate a corridor without collision. The robot is expected to make stops on the way to the debris corner. When the robot reaches the area of the debris it is required to pluck a red cloth attached to the debris then carry it up to transport it to the point where it started. If the robot fails to pluck the red cloth it is required to make a sound which will be a warning to the humans. If it succeeds the robot walks back with the debris. Task analysis The robot will start from an open end of a building with flat stairs meant for wheelchairs and travel along the corridor to the basement. It will be sending signals to the operator who will be seeing the region the robot has reached. What follows will be to take photographs of the debris then sing happy birthday twice to show that it has reached the area of the debris. It will be required to pick up the debris after removing the cloth. The behavior of removing the cloth should be accurate because any mistake will be catastrophic incase of a bomb. This is done by measuring the movement of the robot as well as computing the ability of the robot to grasp the cloth. After removing the cloth it will pick the debris rotate around to face the direction it was coming from. Description of the solution The robot was able to move to the corner where it identified the debris which it picked up. The turtle robot movements were slow but they achieved what was intended to be achieved. If correctly developed, autonomous robots are able to go places where it is unfeasible for humans to go as well as collect data in a timely and effective manner. The primary challenge with these robots is finding the right algorithm for unknown environments. If the robot is programmed in an ineffective manner, data collect and response to its environment will not be beneficial to user. The Turtlebot based on genetic algorithms are the future of the oil and gas industry. The author came to this conclusion after considering the vast amount of undersea area that remains largely unexplored. This seems like a feasible solution because if developed properly, these robots can easily adapt to new terrain and offer developers faster feedback as to the feasibility and potential of certain areas. As well, utilizing autonomous robots based on genetic algorithms will allow companies to explore areas which are too dangerous for human exploration thus aiding in new discoveries. The following is a flowchart for the activities of the TurtleBot The turtlebot robot will have a front and back leg which link together with one rod to make the same movement as shown in the figure below. The leg will be is controlled by a motor that will assist it have a forward, turnaround and backward movements. Experiment results The performance of the robot was done by carrying out five possible trials which took fifteen minutes each. At the beginning, the robot was placed at the entrance door facing the direction of the route to be used by the robot. There was 12 centimeters between the robot and the wall which meant that the robot will not collide with the wall. The movement from the opening to the debris corner the robot was required to take small strides to the corner without colluding with the wall. The robot was successive at the forth trial to remove the red cloth and pick up the debris with minimum force. During the time of travelling towards the debris at the far end of the corner measurements were taken every second. The aim was to discover the strides taken by the robot towards the debris. The graph below shows the time taken and strides made towards the debris. However this experiment was confined to a small area not a large building for the purposes of accuracy. It was discovered that it was easier to drive turtlebot across the building to a certain corner. In most instances the robot missed the red cloth or the debris because there were low-lying objects. However there was proper communication between the controller and the robot. The partitions of the walls played an important role in determining the success of the robot in reaching the target object as well as making a turn around. At a corner it was difficult for the robot to make a turn around without making backward steps before turning around. The following table shows the test results of the robot:- Trial Success Rate Execution Time Feedback Success Rate Trial 1 60% 12 seconds It was able to avoid all obstacles but unstable while moving towards the object. Trial 2 75% 15 seconds Moved with success without hitting the wall. It also reached the object and attempted to remove the red cloth. Trial 3 90% 17 seconds It was successful in reaching the target picking up the object but failed to color out the command of removing the cloth Trial 4 95% 25 seconds It was successful in carrying out all the activities except when it tried to turn around without making a step backward. Trial 5 100% 30 seconds It carried all the activity successfully without failure although it took longer time. The graph below represents the success rate and the time taken:- For source codes Use the attached files The source codes have been developed using the hardware libraries in ROS and C++ and they implement primitives and events. ROS code to control the movement of turtlebot: 1 #! /usr/bin/python 2 import roslib 3 roslib.load_manifest('mm_teleop') 4 5 import rospy 6 import actionlib 7 from actionlib_msgs.msg import * 8 from turtletle_controllers_msgs.msg import * 9 from geometry_msgs.msg import * 10 11 rospy.init_node('move_the_body', anonymous=True) 12 13 client = actionlib.SimpleActionClient( 14 '/body_traj_controller/point_body_action', PointbodyAction) 15 client.wait_for_server() 16 17 g = PointbodyGoal() 18 g.target.body.frame_id = 'base_link' 19 g.target.point.x = 1.0 20 g.target.point.y = 0.0 21 g.target.point.z = 1.0 22 g.min_duration = rospy.Duration(1.0) 23 24 client.send_goal(g) 25 client.wait_for_result() 26 27 if client.get_state() == GoalStatus.SUCCEEDED: ROS code to control the pickup of turtlebot Lunary relations = turtlebot, building, debris binary equivalent relations = fisConnectable, isConnectedg binary relations = fisIng Actions move(d; r) buiding: a precond: basement(a) ^ isIn(r; a) effects: :isIn(r; a) ^ inIn(r; d) take(res) building: a precond: resource(res) ^ region(a) ^ isIn(res; a) effects: :isIn(res; a) ^ :resource(res) fill1(d; s) precond: region(d) ^ region(s) effects: ; fill2(d; s) precond: basement(d) ^ debris(s) effects: isConnected(d; s) build1(d) Methods task: movementbasement(d; s) precond: basement(d) ^ debris(s) ^ ispicked(d; s) subtasks: hi remove-redcloth(d; s) task: moveback(d; s) locals: t; rob; roba; res1; res1a; res2; res2a precond: region(d) ^ region(s) ^ region(t) ^ robot(rob) ^ region(roba) ^ isIn(rob; roba) ^ resource(res1) ^ region(res1a) ^ isIn(res1; res1a) ^ resource(res2) ^ region(res2a) ^ isIn(res2; res2a) ^ :same(res1; res2) ^ :same(t; s) ^ isConnected(s; roba) ^ isConnected(s; res1a) ^ isConnected(s; res2a) ^ isConnectable(s; t) ^ :isConnected(s; t) subtasks: htake(res1), fill1(t; s), take(res2), fill2(t; s), connectRegions(d; t)i move-robot(d) task: moveRobot(d) #!/usr/bin/env python import roslib; roslib.load_manifest('FullScreen') import rospy from sensor_msgs.msg import CompressedImage import pygame # The PyGame screen object screen = None # Screen reoslution screen_size = (0,0) # Flag to indicate when the user has requested we shutdown running = True def save_image(msg): """Save an image to disk. Return the file name.""" if msg.format == "jpeg": tmp_name = "/tmp/pr2cam.jpeg" else: tmp_name = "/tmp/pr2cam.png" tmp_file = open(tmp_name,'wb') tmp_file.write(msg.data) tmp_file.close() return tmp_name def show_image(msg): """Show an image fullscreen using PyGame.""" global screen, screen_size, running # Save the image to a temporary file tmp_name = save_image(msg) # Load the temporary image into PyGame try: frame = pygame.image.load(tmp_name).convert() pygame.transform.scale(frame, screen_size, screen) pygame.display.update() except Exception as e: if running: raise e def init_pygame(): """Initialize PyGame and get screen resolution.""" global screen, screen_size pygame.init() screen = pygame.display.set_mode(screen_size, pygame.HWSURFACE | pygame.DOUBLEBUF | pygame.FULLSCREEN) screen_size = screen.get_size() def handle_events(): """Return False when the user hits the escape key.""" for event in pygame.event.get(): if event.type == pygame.KEYDOWN and event.key == pygame.K_ESCAPE: return False elif event.type == pygame.QUIT: return False return True if __name__ == '__main__': try: init_pygame() rospy.init_node('FullScreen') default_topic = '/wide_stereo/right/image_rect_color/compressed' cam_topic = rospy.get_param('~cam', default_topic) rospy.Subscriber(cam_topic, CompressedImage, show_image) while handle_events() and not rospy.is_shutdown(): rospy.sleep(0.5) running = False pygame.quit() except rospy.ROSInterruptException: pass Discussion of difficulties encountered In the first place, there are limitations that are being encountered in the quest to implement the project. When detecting obstacles on the way the robot had to send signal back where commands had to be given to change direction without this collision was likely to experience. In the first place, it is obvious that these machines are going to take up the place of man, and thereby locking several employment opportunities from man. For instance, conclusive development of robotics is likely to spur on the increased preference of computerized machines to human personnel, in the vehicle assembly industry. While it is true that some gains such as lower employee turnover, low operational costs, abatement of industrial accidents and increased productivity may be cited as the gains for the introduction of robotic applications in this industry, yet, the socioeconomic drawbacks of this move are likely to be very serious. As these computers take over the job market, many people are bound to be locked out of employment. This is certainly bound to be untold catalogues of miseries as people forfeit their means of livelihood to machines. Financial constraints, the straining of the family unit and its widespread disintegration are likely to rock any civilization that goes this path. In respect to the facts disclosed above, the thesis statement that by providing computer systems with AI, the world will be able to solve most of the problems which take on a cognitive aspect only remains lucid in the field of IT. It is highly debatable if the socioeconomic fabric will remain as strong as it is, after the full adoption of AI. The robot is supposed to be involved; Planning. Planning to make movement is task that requires an immense amount of engineering and analysis hence Turtlebot has proved to be good in making movements and picking up items. Operation Problem Solving- During the movement process, problems usually arise while shifting through various velocities. Sensors are responsible for transmitting data to operators alerting them to conditions in real time data. In addition to real time, well reports are taken and stored as cases in order to advise on any similar situation/problems in the future. Pattern Recognition- Normally, any pattern that is abnormal makes up a case. When a new problem occurs, the case is stored for future reference. Al though this approach is effective when there are a small amount of cases involved it can get harder to keep track of as the amount of cases continue to expand and grow. In most case problems are placed in sequence in terms of being able to automatically assess risks and highlight possible problems. Summary of solution The whole idea was to control the movement of the TurtleBot by moving the whole body as well as pick up something from a remote corner. The user was to monitor the performance of this tasks by receiving various forms. The study was done using ROS and C++, this helps in programming the movement without difficulties. The set up of the robot determined the effective performance of this robot in the tasks of movement and taking up an object. We did generate codes for these movements including the act of picking up of the debris. We were able to control turtle to the point it performed its duties after 5 runs or trials. There was no collision with any obstacle during the period. Conclusion The paper aimed at designing a behavior of a robot to perform an act of accessing interior basement of a building to such for a bomb that has been planted. The robot will access the area without the help of human beings but the operator will select an interface which will allow the robot to access the right place. In the experiment the robot was allowed to walk down stairs into a narrow corner where debris was placed to act as a bomb. The robot was monitored to see the movement of its arms, thighs, shank of the body and the forehead. These movements were critical in ensuring that the robot was able to reach the area that was required. Future direction Designed robot that can escape from a building that has a bomb scare at the basement can be used in futute to help human access basement of buildings where bombs have been placed. The movements taken in this assignment were to test the ability of the TurtleBot to access. The remote area of the building is accessed with minimum collision and distraction from dangerous substances within the building. The designed autonomous robot operates autonomously with limited support from human beings and can access interior places including the space. However, there could be a problem in trying to access some areas which may have catastrophic impacts on humans such as places of nuclear reactors. Small mistake will cause a great impact in the environment. Read More

However, incorporating programming into the robot controls will optimize the activities of the robot with minimal or no human interference. Programming will allow autonomous robots to select certain paths and make decisions that will optimize outcomes. In addition, more attention is also being placed on designing autonomous robots so that they are able to effectively interact with one another without disrupting work flows and processes. Programming a TurtleBot will make it possible to perform tasks effectively; the robots are required to avoid obstacles, cover the terrain effectively and carry the workload.

Task statement The robot will be required to find debris situated in a certain corner of a building. This means the robot will carry out various tasks like making movement finding debris taking it up and walking to the same position it was. The root will be required to make a sound once it finds the debris. When it picks it up it is required to sing happy birthday song. This means the robot will be required to navigate a corridor without collision. The robot is expected to make stops on the way to the debris corner.

When the robot reaches the area of the debris it is required to pluck a red cloth attached to the debris then carry it up to transport it to the point where it started. If the robot fails to pluck the red cloth it is required to make a sound which will be a warning to the humans. If it succeeds the robot walks back with the debris. Task analysis The robot will start from an open end of a building with flat stairs meant for wheelchairs and travel along the corridor to the basement. It will be sending signals to the operator who will be seeing the region the robot has reached.

What follows will be to take photographs of the debris then sing happy birthday twice to show that it has reached the area of the debris. It will be required to pick up the debris after removing the cloth. The behavior of removing the cloth should be accurate because any mistake will be catastrophic incase of a bomb. This is done by measuring the movement of the robot as well as computing the ability of the robot to grasp the cloth. After removing the cloth it will pick the debris rotate around to face the direction it was coming from.

Description of the solution The robot was able to move to the corner where it identified the debris which it picked up. The turtle robot movements were slow but they achieved what was intended to be achieved. If correctly developed, autonomous robots are able to go places where it is unfeasible for humans to go as well as collect data in a timely and effective manner. The primary challenge with these robots is finding the right algorithm for unknown environments. If the robot is programmed in an ineffective manner, data collect and response to its environment will not be beneficial to user.

The Turtlebot based on genetic algorithms are the future of the oil and gas industry. The author came to this conclusion after considering the vast amount of undersea area that remains largely unexplored. This seems like a feasible solution because if developed properly, these robots can easily adapt to new terrain and offer developers faster feedback as to the feasibility and potential of certain areas. As well, utilizing autonomous robots based on genetic algorithms will allow companies to explore areas which are too dangerous for human exploration thus aiding in new discoveries.

The following is a flowchart for the activities of the TurtleBot The turtlebot robot will have a front and back leg which link together with one rod to make the same movement as shown in the figure below. The leg will be is controlled by a motor that will assist it have a forward, turnaround and backward movements. Experiment results The performance of the robot was done by carrying out five possible trials which took fifteen minutes each. At the beginning, the robot was placed at the entrance door facing the direction of the route to be used by the robot.

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