This paper proposes two simple schemes for adaptive control of robot manipulator, to achieve trajectory tracking. The state feedback controller consists of feedforward from the reference position trajectory, feedback ...
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This paper proposes two simple schemes for adaptive control of robot manipulator, to achieve trajectory tracking. The state feedback controller consists of feedforward from the reference position trajectory, feedback from the actual trajectory, and an auxiliary input. The feedforward/feedback controller is different from the state feedback controller in that it consists of feedforward from the reference position, velocity, and acceleration trajectory based on “inverse” dynamics of robot manipulator. The feedforward and feedback gains and the auxiliary input are adapted using adaptive control theory based on Lyapunov's direct method, and using only the local information of the corresponding joint. The proposed control schemes are computationally fast and do not require a priori knowledge of the parameter of the manipulator or the payload. Simulation results are presented in support of the proposed schemes.
The authors deal with a measure of static manipulability for a dual-redundant-arm system engaged in cooperative task execution. Considering the kinematic interaction between the two cooperating arms, the dual-arm mani...
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The authors deal with a measure of static manipulability for a dual-redundant-arm system engaged in cooperative task execution. Considering the kinematic interaction between the two cooperating arms, the dual-arm manipulability is defined as the intersection between the two manipulability ellipsoids from individual arms. A task-oriented dual-arm manipulability measure is defined as the measure of geometrical similarity between the desired and the actual dual-arm manipulability ellipsoids at the selected task points. The authors present mathematical formulas defining task-oriented dual redundant arm static manipulability and its application to the optimization of dual-redundant-arm joint as well as grasp configurations. Simulation results are shown.< >
To increase task flexibility in a robotic assembly environment, a hierarchical planning and execution system is being developed which will map user-specified, three-dimensional part assembly tasks into various target ...
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To increase task flexibility in a robotic assembly environment, a hierarchical planning and execution system is being developed which will map user-specified, three-dimensional part assembly tasks into various target robotic workcells, and execute these tasks efficiently using manipulators and sensors available in the workcell. One level of this hierarchy, the supervisor, is responsible for assigning subtasks of a system-generated task plan to a set of task specific specialists, and online coordination of the activity of these specialists to accomplish the user-specified assembly. The design of the supervisor is broken down into five major functional blocks: resource management; concurrency detection; task scheduling; error recovery; and interprocess communication. Using concepts from operating systems, the design of each of these supervisor blocks is examined.< >
The design of the organization level of the intelligent machine as a Boltzmann machine, as described in current neural network literature, is discussed. Since this level is responsible for planning the actions of the ...
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The design of the organization level of the intelligent machine as a Boltzmann machine, as described in current neural network literature, is discussed. Since this level is responsible for planning the actions of the machine, the problem at this tier is formulated as the construction of the right sequence of tasks or events which minimizes the entropy for the desired action. Two search techniques, simulated annealing (SA) and expanding subinterval random search (ESRS), are described. These techniques are used to find the global minimum entropy of a Boltzmann machine. Simulations using these search techniques were conducted using energy as a cost function, and results indicate that ESRS converges faster than SA to a global minimum if the topology contains narrow and deep cost wells.< >
To increase task flexibility in a robotic assembly environment, a hierarchical planning and execution system is being developed which will map user-specified three-dimensional part assembly tasks into various target r...
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To increase task flexibility in a robotic assembly environment, a hierarchical planning and execution system is being developed which will map user-specified three-dimensional part assembly tasks into various target robotic workcells, and execute these tasks efficiently using manipulators and sensors available in the workcell. One level of this hierarchy, the supervisor, is responsible for assigning subtasks of a system-generated task plan to a set of task specific specialists, and online coordination of the activity of these specialists to accomplish the user-specified assembly. The design is broken down into five major functional blocks: resource management; concurrency detection; task scheduling; error recovery; and interprocess communication. The overall function of the supervisor is examined in relation to the other levels of the hierarchical system. The theoretical design of each module of the supervisor is presented and a sample assembly is executed under the supervisor's control.< >
Trajectory planning methods and control algorithms for biped robot steady walking are discussed. The model following plus variable structure systems technique is developed for the control of dynamic walking in the sag...
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Trajectory planning methods and control algorithms for biped robot steady walking are discussed. The model following plus variable structure systems technique is developed for the control of dynamic walking in the sagittal plane. The nonlinear feedback plus modified alpha -computed torque technique is introduced for walking in the frontal plane. simulation results are provided for level walking and ascending on staircases for a five-link biped robot. These results indicate that the proposed algorithms could achieve robust trajectory tracking even in the presence of system modeling errors. Specifically, simulation results show that, even in the presence of disturbances, gait stability can be achieved within two steps after the start of walking. In addition, the biped robot can walk with prespecified patterns.< >
A system is presented which automatically constructs an assembly partial-order graph from an object-oriented model describing parts and their connections. The construction is based on the principle of assembly by disa...
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A system is presented which automatically constructs an assembly partial-order graph from an object-oriented model describing parts and their connections. The construction is based on the principle of assembly by disassembly and on assembly heuristics representing criteria for preferred subassemblies. The system first identifies disassemblable parts and subassemblies by reasoning geometric and physical constraints as well as resource requirements, and then assigns preference to the identified disassembly options based on assembly heuristics. The recursive application of this process to the selected disassemblies results in a hierarchical partial-order graph (HPOG). The HPOG not only specifies the required precedence in part assembly but also provides parallelism for implementing multiple-robot distributed and cooperative assembly. The software is organized under the cooperative-problem-solving paradigm.< >
The authors present a learning expert system which enables a robot to acquire fine motion skills automatically. The system follows the paradigm of Expert Assisted Robot Skill Acquisition (EARSA) proposed by the author...
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The authors present a learning expert system which enables a robot to acquire fine motion skills automatically. The system follows the paradigm of Expert Assisted Robot Skill Acquisition (EARSA) proposed by the authors (1987). EARSA is mainly concerned with the self-discovery of skills by a robot in conjunction with the transfer of human skills to a robot and emphasizes the distinctive difference in perceptual and physical capabilities between a human and a robot. The authors review the theory and mechanism of EARSA, describe the robot fine motion skill learning algorithm formulated on the basis of EARSA, and present the details of simulation on the robot learning of two-dimensional peg-hole insertion skills. The results of simulation indicate the dramatic improvement of performance as a result of skill learning.< >
Quasistatic mechanical systems, in which mass or acceleration is sufficiently small for the inertial term ma in F=ma to be negligible compared to dissipative forces, are discussed. It is pointed out that many instance...
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Quasistatic mechanical systems, in which mass or acceleration is sufficiently small for the inertial term ma in F=ma to be negligible compared to dissipative forces, are discussed. It is pointed out that many instances of robotic manipulation can be well approximated as quasistatic systems, with the dissipative force being dry friction. Energetic formulations of Newton's laws have often been found useful in the solution of mechanics problems involving multiple constraints. An intuitive minimum power principle is outlined which states that a system chooses at every instant the lowest-energy, or 'easiest', motion in conformity with the constraints. Surprisingly, the principle is in general false; but it is proved that the principle is correct in the useful special case that Coulomb friction is the only dissipative or velocity-dependent force acting in the system.< >
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