Cooperative Control of Dual Series Robots

Development in manufacturing, automation, space and underwater exploration has shown vast number of robots being used where most of the existing robots are of coordinated control of a single arm only. Increasing demand for robots application, especially in manufacturing has opened a new challenge; dual arm robot cooperation. This challenge is to develop robots which can carry out greater task which could either be heavy in load or complex in working. The main objectives for this project are to study on the available techniques of cooperative control, to design a program based on the chosen technique, to integrate the program in the system of two existing robot arms handling one common load and to ensure precise tracking of a desired formation and simplicity in its design. The methods being used in this project are performing literature\ud review, selection of cooperative control technique where three cooperative control techniques namely Master/Slave control, Centralized and Decentralized control are compared and implemented to the existing robots, as well as conducting experiment on the real system. Results from the experiment are analyzed and improvised to prove that cooperative control technique could be used for this study. Results from this study are in form of programming of the control system, ladder diagram showing inputs and outputs of the system utilized and calculation of error of relative coordinate of the two robots after experiment execution. In conclusion, master/slave technique has been selected to be most suitable for this study based on its accuracy and simplicity of its design. The objectives for this project have been achieved where no error above lmm recorded which indicates accuracy and number of lines of programming are 21 lines for Master and 16 lines for Slave robot thus, proving its simplicity. However, improvement on the method used could be further studied to minimize number of lines, using other method or extension of this project where rotational motion could be studied

Cooperative Control of Dual Series Robots

Development in manufacturing, automation, space and underwater exploration has shown vast number of robots being used where most of the existing robots are of coordinated control of a single arm only. Increasing demand for robots application, especially in manufacturing has opened a new challenge; dual arm robot cooperation. This challenge is to develop robots which can carry out greater task which could either be heavy in load or complex in working. The main objectives for this project are to study on the available techniques of cooperative control, to design a program based on the chosen technique, to integrate the program in the system of two existing robot arms handling one common load and to ensure precise tracking of a desired formation and simplicity in its design. The methods being used in this project are performing literature review, selection of cooperative control technique where three cooperative control techniques namely Master/Slave control, Centralized and Decentralized control are compared and implemented to the existing robots, as well as conducting experiment on the real system. Results from the experiment are analyzed and improvised to prove that cooperative control technique could be used for this study. Results from this study are in form of programming of the control system, ladder diagram showing inputs and outputs of the system utilized and calculation of error of relative coordinate of the two robots after experiment execution. In conclusion, master/slave technique has been selected to be most suitable for this study based on its accuracy and simplicity of its design. The objectives for this project have been achieved where no error above lmm recorded which indicates accuracy and number of lines of programming are 21 lines for Master and 16 lines for Slave robot thus, proving its simplicity. However, improvement on the method used could be further studied to minimize number of lines, using other method or extension of this project where rotational motion could be studied

Constrained-Differential-Kinematics-Decomposition-Based NMPC for Online Manipulator Control with Low Computational Costs

Flexibility combined with the ability to consider external constraints comprises the main advantages of nonlinear model predictive control (NMPC). Applied as a motion controller, NMPC enables applications in varying and disturbed environments, but requires time-consuming computations. Hence, given the full nonlinear multi-DOF robot model, a delay-free execution providing short control horizons at appropriate prediction horizons for accurate motions is not applicable in common use. This contribution introduces an approach that analyzes and decomposes the differential kinematics similar to the inverse kinematics method to assign Cartesian boundary conditions to specific systems of equations during the model building, reducing the online computational costs. The resulting fully constrained NMPC realizes the translational obstacle avoidance during trajectory tracking using a reduced model considering both joint and Cartesian constraints coupled with a Jacobian transposed controller performing the end-effector’s orientation correction. Apart from a safe distance from the obstacles, the presented approach does not lead to any limitations of the reachable workspace, and all degrees of freedom (DOFs) of the robot are used. The simulative evaluation in Gazebo using the Stäubli TX2-90 commanded of ROS on a standard computer emphasizes the significantly lower online computational costs, accuracy analysis, and extended adaptability in obstacle avoidance, providing additional flexibility. An interpretation of the new concept is discussed for further use and extensions

Introduction to an Efficient Process for Automatic Offline Pro-gram Generation for a Robotic Spot Welding Assembly Line.

One of the most important applications of industrial robots is spot welding which is used in high production applications mostly in automotive industries where mass production is required. The speed, precision, efficiency and the resulting cost reduction due to mass production are well accepted and well documented advantages of automation of spot welding process using robots. In order to meet the new challenges of increased global competition, manufacturers are forced to seek new technologies for improved production and cost reduction. Such cost cutting efforts can only be achieved by improving the offline programming method. Offline programming is one of the most crucial parts of modern automotive manufacturing process. In this Master’s thesis a process was developed for faster and efficient offline programming of industrial manipulators in spot welding application. The thesis work has been conducted in Visual Components Oy, Espoo, Finland. In traditional practice there are lots of manual steps involved in the robotic spot welding area. The whole process design of the robotic spot welding is not simple and includes CAD design of the part, shape and complexity of the parts which needs to be spot weld, design of the robot work cell, design and selection of spot weld gun, required production rate, offline programming tool, robot calibration, work cell calibration, work piece positioner design etc. In this report an approach to implement the offline programming of robot based on simulation software with the process knowledge of car-body in white was proposed and partially developed. Some common problems such as motion simulation, collision detection and calibration can be partly solved by this approach. The thesis consisted of a theoretical section to investigate the current state of art of offline programming tools and methods and a practical section to develop working prototype for demonstration. The implementation of the prototype used the application programmer’s interface (API) available with the simulation software. A prototype was developed to propose an efficient process for putting the whole spot welding process starting for CAD design, work cell setup, offline programming and calibration in a closed loop

Cognitive Reasoning for Compliant Robot Manipulation

Physically compliant contact is a major element for many tasks in everyday environments. A universal service robot that is utilized to collect leaves in a park, polish a workpiece, or clean solar panels requires the cognition and manipulation capabilities to facilitate such compliant interaction. Evolution equipped humans with advanced mental abilities to envision physical contact situations and their resulting outcome, dexterous motor skills to perform the actions accordingly, as well as a sense of quality to rate the outcome of the task. In order to achieve human-like performance, a robot must provide the necessary methods to represent, plan, execute, and interpret compliant manipulation tasks. This dissertation covers those four steps of reasoning in the concept of intelligent physical compliance. The contributions advance the capabilities of service robots by combining artificial intelligence reasoning methods and control strategies for compliant manipulation. A classification of manipulation tasks is conducted to identify the central research questions of the addressed topic. Novel representations are derived to describe the properties of physical interaction. Special attention is given to wiping tasks which are predominant in everyday environments. It is investigated how symbolic task descriptions can be translated into meaningful robot commands. A particle distribution model is used to plan goal-oriented wiping actions and predict the quality according to the anticipated result. The planned tool motions are converted into the joint space of the humanoid robot Rollin' Justin to perform the tasks in the real world. In order to execute the motions in a physically compliant fashion, a hierarchical whole-body impedance controller is integrated into the framework. The controller is automatically parameterized with respect to the requirements of the particular task. Haptic feedback is utilized to infer contact and interpret the performance semantically. Finally, the robot is able to compensate for possible disturbances as it plans additional recovery motions while effectively closing the cognitive control loop. Among others, the developed concept is applied in an actual space robotics mission, in which an astronaut aboard the International Space Station (ISS) commands Rollin' Justin to maintain a Martian solar panel farm in a mock-up environment. This application demonstrates the far-reaching impact of the proposed approach and the associated opportunities that emerge with the availability of cognition-enabled service robots

ALTERNATIVE AND FLEXIBLE CONTROL METHODS FOR ROBOTIC MANIPULATORS: On the challenge of developing a flexible control architecture that allows for controlling different manipulators

Robotic arms and cranes show some similarities in the way they operate and in the way they are designed. Both have a number of links serially attached to each other by means of joints that can be moved by some type of actuator. In both systems, the end-effector of the manipulator can be moved in space and be placed in any desired location within the system’s workspace and can carry a certain amount of load. However, traditional cranes are usually relatively big, stiff and heavy because they normally need to move heavy loads at low speeds, while industrial robots are ordinarily smaller, they usually move small masses and operate at relatively higher velocities. This is the reason why cranes are commonly actuated by hydraulic valves, while robotic arms are driven by servo motors, pneumatic or servo-pneumatic actuators. Most importantly, the fundamental difference between the two kinds of systems is that cranes are usually controlled by a human operator, joint by joint, using simple joysticks where each axis operates only one specific actuator, while robotic arms are commonly controlled by a central controller that controls and coordinates the actuators according to some specific algorithm. In other words, the controller of a crane is usually a human while the controller of a robotic arm is normally a computer program that is able to determine the joint values that provide a desired position or velocity for the end-effector. If we especially consider maritime cranes, compared with robotic arms, they rely on a much more complex model of the environment with which they interact. These kinds of cranes are in fact widely used to handle and transfer objects from large container ships to smaller lighters or to the quays of the harbours. Therefore, their control is always a challenging task, which involves many problems such as load sway, positioning accuracy, wave motion compensation and collision avoidance. Some of the similarities between robotic arms and cranes can also be extended to robotic hands. Indeed, from a kinematic point of view, a robotic hand consists of one or more kinematic chains fixed on a base. However, robotic hands usually present a higher number of degrees of freedom (DOFs) and consequentially a higher dexterity compared to robotic arms. Nevertheless, several commonalities can be found from a design and control point of views. Particularly, modular robotic hands are studied in this thesis from a design and control point of view. Emphasising these similarities, the general term of robotic manipulator is thereby used to refer to robotic arms, cranes and hands. In this work, efficient design methods for robotic manipulators are initially investigated. Successively, the possibility of developing a flexible control architecture that allows for controlling different manipulators by using a universal input device is outlined. The main challenge of doing this consists of finding a flexible way to map the normally fixed DOFs of the input controller to the variable DOFs of the specific manipulator to be controlled. This process has to be realised regardless of the differences in size, kinematic structure, body morphology, constraints and affordances. Different alternative control algorithms are investigated including effective approaches that do not assume a priori knowledge for the Inverse Kinematic (IK) models. These algorithms derive the kinematic properties from biologically-inspired approaches, machine learning procedures or optimisation methods. In this way, the system is able to automatically learn the kinematic properties of different manipulators. Finally, a methodology for performing experimental activities in the area of maritime cranes and robotic arm control is outlined. By combining the rapid-prototyping approach with the concept of interchangeable interfaces, a simulation and benchmarking framework for advanced control methods of maritime cranes and robotic arms is presented. From a control point of view, the advantages of releasing such a flexible control system rely on the possibility of controlling different manipulators by using the same framework and on the opportunity of testing different control approaches. Moreover, from a design point of view, rapidprototyping methods can be applied to fast develop new manipulators and to analyse different properties before making a physical prototype

Enhanced online programming for industrial robots

The use of robots and automation levels in the industrial sector is expected to grow, and is driven by the on-going need for lower costs and enhanced productivity. The manufacturing industry continues to seek ways of realizing enhanced production, and the programming of articulated production robots has been identified as a major area for improvement. However, realizing this automation level increase requires capable programming and control technologies. Many industries employ offline-programming which operates within a manually controlled and specific work environment. This is especially true within the high-volume automotive industry, particularly in high-speed assembly and component handling. For small-batch manufacturing and small to medium-sized enterprises, online programming continues to play an important role, but the complexity of programming remains a major obstacle for automation using industrial robots. Scenarios that rely on manual data input based on real world obstructions require that entire production systems cease for significant time periods while data is being manipulated, leading to financial losses. The application of simulation tools generate discrete portions of the total robot trajectories, while requiring manual inputs to link paths associated with different activities. Human input is also required to correct inaccuracies and errors resulting from unknowns and falsehoods in the environment. This study developed a new supported online robot programming approach, which is implemented as a robot control program. By applying online and offline programming in addition to appropriate manual robot control techniques, disadvantages such as manual pre-processing times and production downtimes have been either reduced or completely eliminated. The industrial requirements were evaluated considering modern manufacturing aspects. A cell-based Voronoi generation algorithm within a probabilistic world model has been introduced, together with a trajectory planner and an appropriate human machine interface. The robot programs so achieved are comparable to manually programmed robot programs and the results for a Mitsubishi RV-2AJ five-axis industrial robot are presented. Automated workspace analysis techniques and trajectory smoothing are used to accomplish this. The new robot control program considers the working production environment as a single and complete workspace. Non-productive time is required, but unlike previously reported approaches, this is achieved automatically and in a timely manner. As such, the actual cell-learning time is minimal