Action module planning and Cartesian based control of an experimental climbing robot

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1997.Includes bibliographical references (leaves 88-95).by David M. Bevly.M.S

Hybrid force and position control in robotic surface processing

PhD ThesisThis programme of research was supported by NEI Parsons Ltd. who sought a robotic means of polishing mechanical components. A study of the problems associated with robot controlled surface processing is presented. From this evolved an approach consistent with the formalisation of the demands of workpiece manipulation which included the adoption of the Hybrid robot control scheme capable of simultaneous force and position control. A unique 3 axis planar experimental manipulator was designed which utilized combined parallel and serial drives. A force sensing wrist was used to measure contact force. A variant of the Hybrid control 'scheme was successfully implemented on a twin computer control system. A number of manipulator control programs are presented. The force control aspect is shown both experimentally and analytically to present control problems and the research has concentrated on this aspect. A general analysis of the dynamics of force control is given which shows force response to be dependent on a number' of important parameters including force sensor, environment and manipulator dynamics. The need for a robust or adaptable force controller is discussed. A series of force controlled manipulator experiments is described and the results discussed in the context of general analyses and specific single degree of freedom simulations. Improvements to manipulator force control are suggested and some were implemented. These are discussed together with their immediate application to the improvement of robot controlled surface processing. This work also lays important foundations for long term related research. In particular the new techniques for actively controlled assembly and force control under 'fast' operation.Science and Engineering Research Council NEI Parsons Ltd

Biomimetic Manipulator Control Design for Bimanual Tasks in the Natural Environment

As robots become more prolific in the human environment, it is important that safe operational procedures are introduced at the same time; typical robot control methods are often very stiff to maintain good positional tracking, but this makes contact (purposeful or accidental) with the robot dangerous. In addition, if robots are to work cooperatively with humans, natural interaction between agents will make tasks easier to perform with less effort and learning time. Stability of the robot is particularly important in this situation, especially as outside forces are likely to affect the manipulator when in a close working environment; for example, a user leaning on the arm, or task-related disturbance at the end-effector. Recent research has discovered the mechanisms of how humans adapt the applied force and impedance during tasks. Studies have been performed to apply this adaptation to robots, with promising results showing an improvement in tracking and effort reduction over other adaptive methods. The basic algorithm is straightforward to implement, and allows the robot to be compliant most of the time and only stiff when required by the task. This allows the robot to work in an environment close to humans, but also suggests that it could create a natural work interaction with a human. In addition, no force sensor is needed, which means the algorithm can be implemented on almost any robot. This work develops a stable control method for bimanual robot tasks, which could also be applied to robot-human interactive tasks. A dynamic model of the Baxter robot is created and verified, which is then used for controller simulations. The biomimetic control algorithm forms the basis of the controller, which is developed into a hybrid control system to improve both task-space and joint-space control when the manipulator is disturbed in the natural environment. Fuzzy systems are implemented to remove the need for repetitive and time consuming parameter tuning, and also allows the controller to actively improve performance during the task. Experimental simulations are performed, and demonstrate how the hybrid task/joint-space controller performs better than either of the component parts under the same conditions. The fuzzy tuning method is then applied to the hybrid controller, which is shown to slightly improve performance as well as automating the gain tuning process. In summary, a novel biomimetic hybrid controller is presented, with a fuzzy mechanism to avoid the gain tuning process, finalised with a demonstration of task-suitability in a bimanual-type situation.EPSR