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In this paper, we examine the problem of visibility-aware robot navigation among movable obstacles (VANAMO). A variant of the well-known NAMO robotic planning problem, VANAMO puts additional visibility constraints on robot motion and object movability. This new problem formulation lifts the restrictive assumption that the map is fully visible and the object positions are fully known. We provide a formal definition of the VANAMO problem and propose the Look and Manipulate Backchaining (LAMB) algorithm for solving such problems. LAMB has a simple vision-based API that makes it more easily transferable to real-world robot applications and scales to the large 3D environments. To evaluate LAMB, we construct a set of tasks that illustrate the complex interplay between visibility and object movability that can arise in mobile base manipulation problems in unknown environments. We show that LAMB outperforms NAMO and visibility-aware motion planning approaches as well as simple combinations of them on complex manipulation problems with partial observability
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Park Rangers’ Problem: Motion Planning for Sequential Visibility Requirements
Many robot tasks may involve achieving visibility (such as to observe areas of interest) or maintaining occlusion (such as to avoid disturbing other agents). We generally formulate such sequential visibility tasks for 3D worlds, termed the Park Rangers’ Problem, and we develop an approach to solve such tasks offering completeness under certain requirements. Our approach constructs an abstraction based on an exact test for visibility between areas, and multiple tests and relaxations for the nonconvex problem of determining occlusions between areas. We apply a constraint-based planning approach and iteratively refine the abstraction. Finally, we evaluate the approach on simulated visibility scenarios.
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- Award ID(s):
- 2124010
- PAR ID:
- 10543255
- Publisher / Repository:
- Springer Proceedings in Advanced Robotics
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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