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This research advances multi-robot coordination by integrating perception, comprehension, and conflict prediction to optimize locomotion in shared industrial spaces. The framework demonstrates a significant performance leap over baseline methods, achieving perfect task success while eliminating safety stops and maintaining optimal inter-robot distances. Such improvements are critical for deploying collaborative mobile cobots safely within complex, dynamic environments without relying on rigid priority rules.
Source coveringarXiv
What this isA model's reading of the article and related coverage, written for aiqbench. Not the publisher's words.

Situation Aware Locomotion for Dual Mobile Cobots in Shared Environments

arXiv2 min read

arXiv:2609.26083v1 Announce Type: new Abstract: This paper presents a situation aware locomotion framework for two mobile collaborative robots operating in shared industrial environments. The proposed method models situation awareness through perception, comprehension, and projection to support locomotion decisions. Robot pose, load state, manipulator state, shared zone occupancy, obstacle state, and predicted inter robot conflict were used to select safe locomotion actions. The framework was implemented in simulation and evaluated in simulated industrial scenarios designed to match a feasible 4 m by 4 m physical test area. The proposed method was compared with two other baselines over multiple trials and randomized seeds. The results show that the situation aware method achieved 100% task success across all scenarios, while the independent and fixed priority baselines each achieved 33.3% overall success. The proposed method eliminated shared zone conflicts and safety stops, maintained the largest average minimum inter robot distance, and completed the tasks with the lowest average completion time. These results indicate that situational awareness can improve the locomotion of dual robots by combining load state, manipulator state, reasoning about the shared zone, and prediction of short-horizon conflicts.

Abstract:This paper presents a situation aware locomotion framework for two mobile collaborative robots operating in shared industrial environments. The proposed method models situation awareness through perception, comprehension, and projection to support locomotion decisions. Robot pose, load state, manipulator state, shared zone occupancy, obstacle state, and predicted inter robot conflict were used to select safe locomotion actions. The framework was implemented in simulation and evaluated in simulated industrial scenarios designed to match a feasible 4 m by 4 m physical test area. The proposed method was compared with two other baselines over multiple trials and randomized seeds. The results show that the situation aware method achieved 100% task success across all scenarios, while the independent and fixed priority baselines each achieved 33.3% overall success. The proposed method eliminated shared zone conflicts and safety stops, maintained the largest average minimum inter robot distance, and completed the tasks with the lowest average completion time. These results indicate that situational awareness can improve the locomotion of dual robots by combining load state, manipulator state, reasoning about the shared zone, and prediction of short-horizon conflicts.

Robotics (cs.RO)

arXiv:2609.26083 [cs.RO]

(or arXiv:2609.26083v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2609.26083 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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Full text under the publisher's open licence · 273 words

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