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Dynamic Re-partitioning for Multi-Robot Coverage
Advisor Information
Raj Dasgupta
Location
UNO Criss Library, Room 231
Presentation Type
Oral Presentation
Start Date
7-3-2014 9:45 AM
End Date
7-3-2014 10:00 AM
Abstract
We consider the problem of coverage path planning in an initially unknown or partially known environment using multiple robots. Previously, Voronoi partitioning has been proposed as a suitable technique for coverage path planning where the free space in the environment is partitioned into non-overlapping regions called Voronoi cells based on the initial positions of the robots, and one robot is allocated to perform coverage in each region. However, a crucial problem while using such a partitioning scheme in an environment where the location of obstacles is not known a priori is that, while performing coverage, a robot might perceive an obstacle that occludes its access to portions of its Voronoi cell and prevents it from completely covering its allocated region. This would either result in portions of the environment remaining uncovered or requires additional path planning by robots to cover the disconnected regions. To address this problem, we propose a novel algorithm that allows robots to coordinate the coverage of inaccessible portions of their Voronoi cell with robots in neighboring Voronoi cells so that each robot is responsible for covering a set of contiguous connected regions. We have proved analytically that our proposed algorithm guarantees complete, non-overlapping coverage. We have also quantified the performance of our algorithm on e-puck robots within the Webots simulator in different environments with different obstacle geometries and shown that it performs complete, non-overlapping coverage.
Dynamic Re-partitioning for Multi-Robot Coverage
UNO Criss Library, Room 231
We consider the problem of coverage path planning in an initially unknown or partially known environment using multiple robots. Previously, Voronoi partitioning has been proposed as a suitable technique for coverage path planning where the free space in the environment is partitioned into non-overlapping regions called Voronoi cells based on the initial positions of the robots, and one robot is allocated to perform coverage in each region. However, a crucial problem while using such a partitioning scheme in an environment where the location of obstacles is not known a priori is that, while performing coverage, a robot might perceive an obstacle that occludes its access to portions of its Voronoi cell and prevents it from completely covering its allocated region. This would either result in portions of the environment remaining uncovered or requires additional path planning by robots to cover the disconnected regions. To address this problem, we propose a novel algorithm that allows robots to coordinate the coverage of inaccessible portions of their Voronoi cell with robots in neighboring Voronoi cells so that each robot is responsible for covering a set of contiguous connected regions. We have proved analytically that our proposed algorithm guarantees complete, non-overlapping coverage. We have also quantified the performance of our algorithm on e-puck robots within the Webots simulator in different environments with different obstacle geometries and shown that it performs complete, non-overlapping coverage.