Collaborative Object Transportation by Multiple Robots with Onboard Object Localization Algorithm

Hu, Zhixian; Zhao, Zhixiang; Zhang, Lianxin; Liu, Hengli; Ding, Ning; Sun, Zhenglong; Lam, Tin Lun; Qian, Huihuan

doi:10.1109/robio49542.2019.8961823

Cited by 4 publications

(1 citation statement)

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“…Hu et al propose an onboard transported object localization algorithm in cooperative object transport tasks [102]. Unlike the previous method that uses an additional localization device for the transported object, this algorithm merges the scan data from robots' LIDAR to provide real-time object position.…”

Section: ) Transport Object Localizationmentioning

confidence: 99%

Multi-Robot Systems and Cooperative Object Transport: Communications, Platforms, and Challenges

Lin

et al. 2023

IEEE Open J. Comput. Soc.

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Multi-robot systems gain considerable attention due to lower cost, better robustness, and higher scalability as compared with single-robot systems. Cooperative object transport, as a well-known use case of multi-robot systems, shows great potential in real-world applications. The design and implementation of a multi-robot system involve many technologies, specifically, communication, coordination, task allocation methods, experimental platforms, and simulators. However, most of recent multi-robot system studies focus on coordination and task allocation problems, with little focus on communications among multiple robots. In this review, we focus on the communication, validation platform, and simulator of multi-robot systems, and discuss one of the important applications, cooperative object transport. First, we study the multi-robot system fundamentals and comprehensively review the multi-robot system communication technologies. Then, the multi-robot system validating platform, testbed, simulator, and middleware used in academia and industry are investigated. Finally, we discuss recent advances in cooperative object transport, and challenges and possible future research directions for multi-robot systems.

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Section: ) Transport Object Localizationmentioning

confidence: 99%