A motion strategy for exploration driven by an automaton activating feedback-based controllers


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.

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    Note that this is the configuration space for a translating disc rather than for a rigid body because of rotational symmetry.

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    A reflex vertex is a polygon vertex of an internal angle greater than \(\pi \).


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Correspondence to Rafael Murrieta-Cid.

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This work was partially funded by CONACYT Projects 220796 and 264896. The authors would also like to acknowledge the financial support of Intel Corporation for the development of this work.

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Martinez, E., Laguna, G., Murrieta-Cid, R. et al. A motion strategy for exploration driven by an automaton activating feedback-based controllers. Auton Robot 43, 1801–1825 (2019). https://doi.org/10.1007/s10514-019-09835-6

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  • Exploration
  • Combinatorial filters
  • Feedback controllers
  • Nonholonomic constraints