منابع مشابه
Near-Minimum-Time Motion Planning of Manipulators along Specified Path
The large amount of computation necessary for obtaining time optimal solution for moving a manipulator on specified path has made it impossible to introduce an on line time optimal control algorithm. Most of this computational burden is due to calculation of switching points. In this paper a learning algorithm is proposed for finding the switching points. The method, which can be used for both ...
متن کاملPath Planning in Expansive Con guration Spaces
We introduce the notion of expansiveness to characterize a family of robot connguration spaces whose connectivity can be eeectively captured by a roadmap of randomly-sampled milestones. The analysis of expansive connguration spaces has inspired us to develop a new randomized planning algorithm. This new algorithm tries to sample only the portion of the connguration space that is relevant to the...
متن کاملAdaptive Informative Path Planning in Metric Spaces
In contrast to classic geometric motion planning, informative path planning (IPP) seeks a path for a robot to sense the world and gain information. In adaptive IPP, the robot chooses the next sensing location conditioned on all information acquired so far, and the robot’s goal is to minimize the travel cost required for identifying a true hypothesis. Adaptive IPP is NP-hard, because the robot m...
متن کاملPath planning in expansive configuration spaces
We introduce the notion of expansiveness to characterize a family of robot conngu-ration spaces whose connectivity can be eeectively captured by a roadmap of randomly-sampled milestones. The analysis of expansive connguration spaces has inspired us to develop a new randomized planning algorithm. This new algorithm tries to sample only the portion of the connguration space that is relevant to th...
متن کاملMotion Planning in Non-Gaussian Belief Spaces
In environments with information symmetry, uncertain or ambiguous data associations can lead to a multi-modal hypothesis on the robot’s state. Thus, a planner cannot simply base actions on the most-likely state. We propose an algorithm that uses a Receding Horizon Planning approach to plan actions that sequentially disambiguate a multi-modal belief to a uni-modal Gaussian and achieve tight loca...
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ژورنال
عنوان ژورنال: Robotics and Autonomous Systems
سال: 2018
ISSN: 0921-8890
DOI: 10.1016/j.robot.2018.08.012