Multi-Robot Search and Rescue: A Potential Field Based Approach

Baxter, Joseph L.; Burke, Edmund K.; Garibaldi, Jonathan M.; Norman, Mark

doi:10.1007/978-3-540-73424-6_2

Cited by 121 publications

(65 citation statements)

References 14 publications

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“…Several researchers have investigated potential field approach for decentralized multirobotic control and coverage (Baxter et al 2007). In the potential field approach, robots feels force of attraction for the goal (e.g.…”

Section: Related Workmentioning

confidence: 99%

A Cognitive Agent-based Model for Multi-Robot Coverage at a City Scale

Zia

Din

Shahzad

et al. 2017

Complex Adapt Syst Model

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Background In this article, we model a behavior-based strategy of autonomous coverage and exploration at the scale of a city with multiple robots. The behavioral components are motivated by Cepeda et al. (Sensors 12 (9): 12772–12797, 2012) and extended to incorporate into a generic cellular-automata based agent model. These agents are representing homogenous robots with reactive control. Deliberative approaches requires large scale map and large memory, which slowdowns the execution. Our approach is reactive and simple, that is, robots have no prior information about the environment and do not generate a route map as they traverse. However, other robots in neighborhood are detected using local sensors. Findings A city-scale map-driven simulation is designed and model’s efficiency is evaluated for different deployment possibilities. It is evidenced that even with this simple model, the agents are able to explore a significant percentage of the environment. Conclusion For a city-scale multi-robotic exploration, our simple but efficient model does not require explicit communication and data sharing (and hence representation and storage of navigated map) because possibility of encountering and influencing another agent is quite low, due to spatial dynamics of the environment.

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Section: Related Workmentioning

confidence: 99%

A Cognitive Agent-based Model for Multi-Robot Coverage at a City Scale

Zia

Din

Shahzad

et al. 2017

Complex Adapt Syst Model

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“…Similar approaches include that of Lau [10], Julia et al [12], Renzaglia [13], Baxter [14], Cepeda [15] and Popa [16]. Baxter [14] presents a potential field approach in which the field is shared among robots. Cepeda [15] proposed a behavior based approach for multi-robot exploration, but such an approach has difficulty in robot exploration status synchronization.…”

Section: Prior Workmentioning

confidence: 99%

Leveraging area bounds information for autonomous decentralized multi-robot exploration

Liu

Lyons

2015

Robotics and Autonomous Systems

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h i g h l i g h t s• A uniform, decentralized, potential-field based approach to dispersing a team of robots to explore an area quickly.• Leverages knowledge of the overall bounds of the area to be explored and includes a monotonic coverage factor in the field equations to avoid minima.• Allows robot team members to become disconnected from and reconnected with the team and ongoing dispersion strategy.• Introduces performance metrics for team speedup and efficiency in the case of adding members to teams.• Presents both simulation and experimental robot results. a r t i c l e i n f o t r a c tThis paper proposes a simple and uniform, decentralized approach to the problem of dispersing a team of robots to explore an area quickly. The Decentralized Space-Based Potential Field (D-SBPF) algorithm is a potential field approach that leverages knowledge of the overall bounds of the area to be explored. It includes a monotonic coverage factor in the potential field to avoid minima, realistic sensor bounds, and a distributed map exchange protocol.The D-SBPF approach yields a simple potential field control strategy for all robots but nonetheless has good dispersion and overlap performance in exploring areas with convex geometry while avoiding potential minima. Both simulation and robot experimental results are included as evidence, and performance, speedup and efficiency metrics for each are presented.

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“…Ge and Cui (2002) included velocity terms for target and obstacles within APF to compute potential to correct the problem of GNRON. Baxter et al (2007Baxter et al ( , 2009 Until now in the literature, very few studies associated with the path planning of USV have made use of the APF in a practical marine environment. Most of these studies have been conducted in selfsimulated environment.…”

Section: Introductionmentioning

confidence: 99%