Decentralized Adaptive Control of Manipulators
This paper presents two new adaptive schemes for motion control of robot manipulators.
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This paper presents two new adaptive schemes for motion control of robot manipulators.
This paper addresses the motion and force control problem of multiple robot arms manipulating a cooperatively held object. A general control paradigm is introduced which decouples the motion and force control problems. For motion control, different control strategies are constructed based on the variables used as the control input in the controller design. There are three natural choices; acceleration of a generalized coordinate, arm tip force vectors, and the joint torques. The first two choices require full model information but produce simple models for the control design problem. The last choice results in a class of relatively model independent control laws by exploiting the Hamiltonian structure of the open loop system. The motion control only determines the joint torque to within a manifold, due to the multiple-arm kinematic constraint. To resolve the nonuniqueness of the joint torques, two methods are introduced. If the arm and object models are available, an optimization can be performed to best allocate the desired and effector control force to the joint actuators. The other possibility is to control the internal force about some set point. It is shown that effective force regulation can be achieved even if little model information is available.
A general gross and fine motion planning and control strategy is needed for lightweight robotic manipulator applications such as painting, welding, material handling, surface finishing, and spacecraft servicing. The control problem of lightweight manipulators is to perform fast, accurate, and robust motions despite the payload variations, structural flexibility, and other environmental disturbances. Performance of the rigid manipulator model based computed torque and decoupled joint control methods are determined and simulated for the counterpart flexible manipulators. A counterpart flexible manipulator is defined as a manipulator which has structural flexibility, in addition to having the same inertial, geometric, and actuation properties of a given rigid manipulator. An adaptive model following control (AMFC) algorithm is developed to improve the performance in speed, accuracy, and robustness. It is found that the AMFC improves the speed performance by a factor of two over the conventional non-adaptive control methods for given accuracy requirements while proving to be more robust with respect to payload variations. Yet there are clear limitations on the performance of AMFC alone as well, which are imposed by the arm flexibility. In the search to further improve speed performance while providing a desired accuracy and robustness, a combined control strategy is developed. Furthermore, the problem of switching from one control structure to another during the motion and implementation aspects of combined control are discussed.
This paper describes work underway to evaluate the effectiveness of voice recognition systems as an element in the control of a robotic welding workcell. Factors being considered for control include program editor access security, preoperation checklist requirements, welding process variable control, and robot manipulator motion overrides. In the latter two categories, manual vocal control is being compared against manual tactile control and fully automatic control in terms of speed of response, accuracy, stability, reliability, and safety.
Several approaches to complicated control problem examined. Report surveys methods for controlling motion of robot manipulators. Applies to coupled, highly nonlinear multiple-link robots. Presents adaptive control technique based on discrete linear model of robot arm, obtained by linearizing nonlinear dynamical equations about nominal trajectory. Parameters of model calculated with adaptive parameter-identification algorithm. Based on system model, optimal control input computed using position and velocity feedback.
Gross motion control of robotic manipulators typically requires significant on-line computations to compensate for nonlinear dynamics due to gravity, Coriolis, centripetal, and friction nonlinearities. One controller proposed by Luo and Saridis avoids these computations by feeding back joint acceleration and torque. This study implements the controller on a Puma 600 robotic manipulator. Joint acceleration measurement is obtained by measuring linear accelerations of each joint, and deriving a computationally efficient transformation from the linear measurements to the angular accelerations. Torque feedback is obtained by using the previous torque sent to the joints. The implementation has stability problems on the Puma 600 due to the extremely high gains inherent in the feedback structure. Since these high gains excite frequency modes in the Puma 600, the algorithm is modified to decrease the gain inherent in the feedback structure. The resulting compensator is stable and insensitive to high frequency unmodeled dynamics. Moreover, a second compensator is proposed which uses acceleration and torque feedback, but still allows nonlinear terms to be fed forward. Thus, by feeding the increment in the easily calculated gravity terms forward, improved responses are obtained. Both proposed compensators are implemented, and the real time results are compared to those obtained with the computed torque algorithm.
Fine motions of robotic manipulator controlled with help of visual feedback by new method reducing position errors by order of magnitude. Robotic vision subsystem includes five cameras: three stationary ones providing wide-angle views of workspace and two mounted on wrist of auxiliary robot arm. Stereoscopic cameras on arm give close-up views of object and end effector. Cameras measure errors between commanded and actual positions and/or provide data for mapping between visual and manipulator-joint-angle coordinates.
The motions of robotic manipulators mounted on spacecraft can disturb the spacecraft's positions and attitude. These disturbances can surpass the ability of the system's attitude control reaction jets to control them, for the disturbances increase as manipulator speeds increase. If the manipulator moves too quickly the resulting disturbances can exceed the saturation levels of the reaction jets, causing excessive spacecraft motions. A method for planning space manipulator's motions is presented, so that tasks can be performed as quickly as possible without saturating the system's attitude control jets.
The motion and force control of multiple robot arms manipulating a commonly held object is addressed. A general control paradigm that decouples the motion and force control problems is introduced. For motion control, there are three natural choices: (1) joint torques, (2) arm-tip force vectors, and (3) the acceleration of a generalized coordinate. Choice (1) allows a class of relatively model-independent control laws by exploiting the Hamiltonian structure of the open-loop system; (2) and (3) require the full model information but produce simpler problems. To resolve the nonuniqueness of the joint torques, two methods are introduced. If the arm and object models are available, the allocation of the desired end-effector control force to the joint actuators can be optimized; otherwise the internal force can be controlled about some set point. It is shown that effective force regulation can be achieved even if little model information is available.
A robot that can duplicate humam motion capabilities in such activities as balancing, reaching, lifting, and moving has been built and tested. These capabilities are achieved through the use of real time Model-Based Control (MBC) techniques which have recently been demonstrated. MBC accounts for all manipulator inertial forces and provides stable manipulator motion control even at high speeds. To effectively demonstrate the unique capabilities of MBC, an experimental robotic manipulator was constructed, which stands upright, balancing on a two wheel base. The mathematical modeling of dynamics inherent in MBC permit the control system to perform functions that are impossible with conventional non-model based methods. These capabilities include: (1) Stable control at all speeds of operation; (2) Operations requiring dynamic stability such as balancing; (3) Detection and monitoring of applied forces without the use of load sensors; (4) Manipulator safing via detection of abnormal loads. The full potential of MBC has yet to be realized. The experiments performed for this research are only an indication of the potential applications. MBC has no inherent stability limitations and its range of applicability is limited only by the attainable sampling rate, modeling accuracy, and sensor resolution. Manipulators could be designed to operate at the highest speed mechanically attainable without being limited by control inadequacies. Manipulators capable of operating many times faster than current machines would certainly increase productivity for many tasks.
A new conceptually simple approach to controlling compliant motions of a robot manipulator is presented. The 'hybrid' technique described combines force and torque information with positional data to satisfy simultaneous position and force trajectory constraints specified in a convenient task related coordinate system. Analysis, simulation, and experiments are used to evaluate the controller's ability to execute trajectories using feedback from a force sensing wrist and from position sensors found in the manipulator joints. The results show that the method achieves stable, accurate control of force and position trajectories for a variety of test conditions.
Collision-free optimal motion and trajectory planning for robotic manipulators are solved by a method of sequential gradient restoration algorithm. Numerical examples of a two degree-of-freedom (DOF) robotic manipulator are demonstrated to show the excellence of the optimization technique and obstacle avoidance scheme. The obstacle is put on the midway, or even further inward on purpose, of the previous no-obstacle optimal trajectory. For the minimum-time purpose, the trajectory grazes by the obstacle and the minimum-time motion successfully avoids the obstacle. The minimum-time is longer for the obstacle avoidance cases than the one without obstacle. The obstacle avoidance scheme can deal with multiple obstacles in any ellipsoid forms by using artificial potential fields as penalty functions via distance functions. The method is promising in solving collision-free optimal control problems for robotics and can be applied to any DOF robotic manipulators with any performance indices and mobile robots as well. Since this method generates optimum solution based on Pontryagin Extremum Principle, rather than based on assumptions, the results provide a benchmark against which any optimization techniques can be measured.
An efficient approach to cartesian motion and force control of a 7 degree of freedom (DOF) manipulator is presented. It is based on extending the active stiffness controller to the 7 DOF case in general and use of an efficient version of the gradient projection technique for solving the inverse kinematics problem. Cooperative control is achieved through appropriate configuration of individual manipulator controllers. In addition, other aspects of trajectory generation using standard techniques are integrated into the controller. The method is then applied to a specific manipulator of interest (Robotics Research T-710). Simulation of the kinematics, dynamics, and control are provided in the context of several scenarios: one pertaining to a noncontact pick and place operation; one relating to contour following where contact is made between the manipulator and environment; and one pertaining to cooperative control.
For space based robots in which the base is free to move, motion planning and control is complicated by uncertainties in the inertial properties of the manipulator and its load. A new adaptive control method is presented for space based robots which achieves globally stable trajectory tracking in the presence of uncertainties in the inertial parameters of the system. A partition is made of the fifteen degree of freedom system dynamics into two parts: a nine degree of freedom invertible portion and a six degree of freedom noninvertible portion. The controller is then designed to achieve trajectory tracking of the invertible portion of the system. This portion consist of the manipulator joint positions and the orientation of the base. The motion of the noninvertible portion is bounded, but unpredictable. This portion consist of the position of the robot's base and the position of the reaction wheel.
The analog control system for positioning each link of the Robotics Research Corporation Model K-1607 robot manipulator was redesigned for computer control. In order to accomplish the redesign, a linearized model of the dynamic behavior of the robot was developed. The parameters of the model were determined by examination of the input-output data collected in closed-loop operation of the analog control system. The robot manipulator possesses seven degrees of freedom in its motion. The analog control system installed by the manufacturer of the robot attempts to control the positioning of each link without feedback from other links. Constraints on the design of a digital control system include: the robot cannot be disassembled for measurement of parameters; the digital control system must not include filtering operations if possible, because of lack of computer capability; and criteria of goodness of control system performing is lacking. The resulting design employs sampled-data position and velocity feedback. The criteria of the design permits the control system gain margin and phase margin, measured at the same frequencies, to be the same as that provided by the analog control system.
Computerized system for controlling motion of linear-track accelerator applied to other automated equipment, such as numerically-controlled machine tools and robot manipulators on assembly lines. System controls motions of sled with sine-wave signal created digitally by microprocessor. Dynamic parameters of sled motion are monitored so sled may be stopped safely if malfunction occurs. Sled is capable of sinusoidal accelerations up to 0.5 g with 125-kg load.
The recent developments of techniques which assist an operator in the control of remote robotic systems are described. In particular, applications are aimed at two specific scenarios: The control of remote robot manipulators; and motion planning for remote transporter vehicles. Common to both applications is the use of realistic computer graphics images which provide the operator with pertinent information. The specific system developments for several recently completed and ongoing telepresence research projects are described.
Improved method of mathematical modeling of dynamics of flexible robotic manipulators developed for use in controlling motions of manipulators. Involves accounting for effect, upon modes of vibration of manipulator, of changes in configuration of manipulator and manipulated payload(s). Flexible manipulator has one or more long, slender articulated link(s), like those used in outer space, method also applicable to terrestrial industrial robotic manipulators with relatively short, stiff links, or to such terrestrial machines as construction cranes.