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• W2140195175 abstract "We consider the problem of a robot manipulator operating in a noisy work space. The robot is assigned the task of moving fromP i toP f . BecauseP i is its initial position, this position can be known fairly accurately. However, becauseP f is usu ally obtained as a result of a sensing operation, possibly vision sensing, we assume thatP f is noisy. We propose a so lution to achieve the motion that involves a new learning automaton, called the Discretized Linear Reward-Penalty (DL RP ) automaton. The strategy we propose does not involve the computation of any inverse kinematics. Alternatively, an automaton is positioned at each joint of the robot, and by processing repeated noisy observations of P f the automata operate in parallel to control the motion of the manipulator." @default.
• W2140195175 created "2016-06-24" @default.
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• W2140195175 date "1991-04-01" @default.
• W2140195175 modified "2023-09-27" @default.
• W2140195175 title "Trajectory Planning of Robot Manipulators in Noisy Work Spaces Using Stochastic Automata" @default.
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• W2140195175 doi "https://doi.org/10.1177/027836499101000205" @default.
• W2140195175 hasPublicationYear "1991" @default.
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