A novel approach towards computing global maps for multi-robotic operations in tactical environments

Ishmael Johnson-Bey; Venkat Dasari

doi:10.1117/12.2557383

22 April 2020 A novel approach towards computing global maps for multi-robotic operations in tactical environments

Ishmael Johnson-Bey, Venkat Dasari

Proceedings Volume 11419, Disruptive Technologies in Information Sciences IV; 1141908 (2020) https://doi.org/10.1117/12.2557383
Event: SPIE Defense + Commercial Sensing, 2020, Online Only

Abstract

During multi-robot simultaneous localization and mapping (SLAM) tasks, a team of robot agents must efficiently synthesize a global map from individual local maps. One method to accomplish this is reserving a subset of robots to perform data fusion and assigning the others to collect and generate local maps. While this solves, the division of labor problem, it requires humans to explicitly designate which robots handle what tasks and it does not scale well to large teams. Moreover, when robots are operating in tactical environments, they may be placed on a heterogeneous team, with limited or unreliable communication infrastructure. To assist with the task of role assignment, we describe a novel decentralized message passing algorithm, for what we are calling Distributed Leader Consensus (DLC). DLC helps a set of agents self-organize into structured groups by giving them the ability to autonomously come to a consensus on the group leader. Our approach is entirely distributed, easily configurable, and is robust to agents being dynamically added to or removed from the system. DLC may be configured to limit group sizes, assign multiple leaders, and select leaders based on computational power and/or physical proximity. We test our approach in simulation by having a set of agents adapt to changing teammate availability.

Conference Presentation

Citation Download Citation

Ishmael Johnson-Bey and Venkat Dasari "A novel approach towards computing global maps for multi-robotic operations in tactical environments", Proc. SPIE 11419, Disruptive Technologies in Information Sciences IV, 1141908 (22 April 2020); https://doi.org/10.1117/12.2557383

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