Sensing and coverage for a network of heterogeneous robots

Pimenta, Luciano C. A.; Kumar, Vijay; Mesquita, Renato C.; Pereira, Guilherme A. S.

doi:10.1109/cdc.2008.4739194

Cited by 226 publications

(176 citation statements)

References 10 publications

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“…Environments with polygonal obstacles are considered in [63,7]. A solution to the multi-agent coverage problem for non-point robots in non-convex environments can be found in [51].…”

Section: Multi-agent Coverage and Spatial Load Balancingmentioning

confidence: 99%

“…A limited sample of work building on this approach includes limited sensor footprints [38], heterogeneous agents (different sensing radii) [59,51], non-holonomic agents [35,18,55], and power constraints [34]. The area-constrained problem is studied in [14,48,49], where a partition of the environment, dependent on weights, is employed.…”

Section: Multi-agent Coverage and Spatial Load Balancingmentioning

confidence: 99%

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Sampling-Based Motion Planning Algorithms for Replanning and Spatial Load Balancing

Boardman¹

2017

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“…Environments with polygonal obstacles are considered in [63,7]. A solution to the multi-agent coverage problem for non-point robots in non-convex environments can be found in [51].…”

Section: Multi-agent Coverage and Spatial Load Balancingmentioning

confidence: 99%

Section: Multi-agent Coverage and Spatial Load Balancingmentioning

confidence: 99%

Sampling-Based Motion Planning Algorithms for Replanning and Spatial Load Balancing

Boardman¹

2017

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“…The cost function is shown to subsume several different kinds of existing coverage cost functions. There has been another extension to heterogeneous groups of finite size robots and non-convex environments in [10]. Standard approaches to Voronoi based coverage control assume simple integrator dynamics for the robots, yielding the ability of traversing both smooth and non-smooth trajectories for robots.…”

Section: Introductionmentioning

confidence: 99%

Decentralized Coverage Control for Multi-Agent Systems with Nonlinear Dynamics

Dirafzoon

Menhaj

Afshar

2011

IEICE Trans. Inf. & Syst.

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SUMMARYIn this paper, we study the decentralized coverage control problem for an environment using a group of autonomous mobile robots with nonholonomic kinematic and dynamic constraints. In comparison with standard coverage control procedures, we develop a combined controller for Voronoi-based coverage approach in which kinematic and dynamic constraints of the actual mobile sensing robots are incorporated into the controller design. Furthermore, a collision avoidance component is added in the kinematic controller in order to guarantee a collision free coverage of the area. The convergence of the network to the optimal sensing configuration is proven with a Lyapunov-type analysis. Numerical simulations are provided approving the effectiveness of the proposed method through several experimental scenarios.

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“…In the context of Voronoi coverage, robot-to-robot collision avoidance for robots of physical size (i.e., finite size instead of zero-sized point robots) has previously been considered by [5,6]. The method in [5] restricts the robots' positions to the collision-free subareas in the interiors of their Voronoi cells; the Voronoi coverage controller in [6] adds a collision avoidance component based on repulsive terms to the coverage control law.…”

Section: Introductionmentioning

confidence: 99%

“…The method in [5] restricts the robots' positions to the collision-free subareas in the interiors of their Voronoi cells; the Voronoi coverage controller in [6] adds a collision avoidance component based on repulsive terms to the coverage control law. Both methods, however, focus on one collision scenario only, which addresses the collision avoidance among robots that all share one single objective and execute the same Voronoi coverage control law cooperatively.…”

Section: Introductionmentioning

confidence: 99%

On Combining Multi-robot Coverage and Reciprocal Collision Avoidance

Breitenmoser

Martinoli

2016

Springer Tracts in Advanced Robotics

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Although robotic coverage and collision avoidance are active areas of robotics research, the avoidance of collision situations between robots has often been neglected in the context of multi-robot coverage tasks. In fact, for robots of physical size, collisions are likely to happen during deployment and coverage in densely packed multi-robot configurations. For this reason, we aim to motivate by this paper the combined use of multi-robot coverage and reciprocal collision avoidance. We present a taxonomy of collision scenarios in multi-robot coverage problems. In particular, coverage tasks with built-in heterogeneity such as multiple antagonistic objectives or robot constraints are shown to benefit from the combination. Based on our taxonomy, we evaluate four representative robotic use cases in simulation by combining the specific methods of Voronoi coverage and reciprocal velocity obstacles.

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Sensing and coverage for a network of heterogeneous robots

Cited by 226 publications

References 10 publications

Sampling-Based Motion Planning Algorithms for Replanning and Spatial Load Balancing

Sampling-Based Motion Planning Algorithms for Replanning and Spatial Load Balancing

Decentralized Coverage Control for Multi-Agent Systems with Nonlinear Dynamics

On Combining Multi-robot Coverage and Reciprocal Collision Avoidance

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