Affordance matching from the shared information in multi-robot

Yi, Chang’an; Min, Huaqing; Luo, Ruiyan

doi:10.1109/robio.2015.7414625

Cited by 3 publications

(1 citation statement)

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“…The current work presents a new idea in which the robots themselves share information about the obstacles encountered in remote areas of the map. Information sharing between robots has been discussed in [ 22 ] in which two robots with different capabilities share information to match affordances, i.e., whether an object is graspable or moveable. Work in [ 23 ] proposes an algorithm which shares corresponding matches of an object over time by two robots to calculate an accurate relative localization.…”

Section: Introductionmentioning

confidence: 99%

Symbiotic Navigation in Multi-Robot Systems with Remote Obstacle Knowledge Sharing

Ravankar

Kobayashi

et al. 2017

Sensors

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Large scale operational areas often require multiple service robots for coverage and task parallelism. In such scenarios, each robot keeps its individual map of the environment and serves specific areas of the map at different times. We propose a knowledge sharing mechanism for multiple robots in which one robot can inform other robots about the changes in map, like path blockage, or new static obstacles, encountered at specific areas of the map. This symbiotic information sharing allows the robots to update remote areas of the map without having to explicitly navigate those areas, and plan efficient paths. A node representation of paths is presented for seamless sharing of blocked path information. The transience of obstacles is modeled to track obstacles which might have been removed. A lazy information update scheme is presented in which only relevant information affecting the current task is updated for efficiency. The advantages of the proposed method for path planning are discussed against traditional method with experimental results in both simulation and real environments.

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Section: Introductionmentioning

confidence: 99%