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 use of multisensor integration and fusion enables a multisensor-based mobile robot to operate in uncertain or unknown dynamic environments. After first distinguishing between multisensor integration and the more r...
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A flexible robotic system with intelligent sensory capability which can be used in an industrial environment to autonomously perform sophisticated manufacturing tasks that are typically done by manual labor is present...
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Issues concerning the effective integration of multiple sensors into the operation of intelligent systems are presented, and a description of some of the general paradigms and methodologies that address this problem i...
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In this paper, the usefulness of applying the complex as well as ordinary moment features for similar object recognition using a tactile array sensor has been explored. Some complex moment invariants have been derived...
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A robotic system that can visually track and intercept an arbitrary object which is traveling at an unknown velocity on a conveyor has been presented. A fiber-optic eye-in-hand vision system developed at NCSU is used ...
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A robotic system that can visually track and intercept an arbitrary object which is traveling at an unknown velocity on a conveyor has been presented. A fiber-optic eye-in-hand vision system developed at NCSU is used as an integral part of the entire tracking system. The eye-in-hand system is used to characterize the object trajectory in real time, using a modified optical flow approach. A control strategy has been developed which utilizes the kinematic data that are extracted by the tracking algorithm to intercept the moving object. An overall system configuration and its basic principles are described. The demonstration of the initial results is presented.< >
A memory-based robotic control paradigm which learns relationships between a control effort and a change of state is introduced. It has been used to develop a learning control system which implements step responses in...
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A memory-based robotic control paradigm which learns relationships between a control effort and a change of state is introduced. It has been used to develop a learning control system which implements step responses in one dimension on a robotic gripper, with partial success. It was found that velocity as well as positional feedback were required to complete even simple movements. It is believed that aspects of this approach would readily extend to a tactile sensing system.< >
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