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A motion strategy for exploration driven by an automaton activating feedback-based controllers
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DOI：10.1007/s10514-019-09835-6.png)
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Abstract
En 中文
This paper addresses the problem of exploring an unknown, planar, polygonal and simply connected environment. To explore the environment, the robot follows the environment boundary. In the first part of this paper, we propose a motion policy based on simple sensor feedback and a complete exploration strategy is represented as a Moore machine. The proposed motion policy is based on the paradigm of avoiding the state estimation; there is a direct mapping from observation to control. We present the theoretical conditions guaranteeing that the robot discovers the largest possible region of the environment. In the second part of the paper, we propose an automaton that filters spurious observations to activate feedback-based controllers. We propose a practical control scheme whose objective is to maintain a desired distance between the robot and the boundary of the environment. The approach is able to deal with imprecise robot's observations and controls, and to take into account variations in the robot's velocities. The control scheme switches controllers according to observations obtained from the robots sensor. Our control scheme aims to maintain the continuity of angular and linear velocities of the robot in spite of the switching between controllers. All the proposed techniques have been implemented and both simulations and experiments in a real robot are presented.
Keywords:
Exploration
Combinatorial filters
Feedback controllers
Nonholonomic constraints
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