Robotics & Machine Learning Daily News2024,Issue(Feb.21) :6-7.DOI:10.1109/TRO.2023.3341689

Study Results from Leibniz University Hannover in the Area of Robotics Reported (Predictive Multi-agent-based Planning and Landing Controller for Reactive Dual-arm Manipulation)

Robotics & Machine Learning Daily News2024,Issue(Feb.21) :6-7.DOI:10.1109/TRO.2023.3341689

Study Results from Leibniz University Hannover in the Area of Robotics Reported (Predictive Multi-agent-based Planning and Landing Controller for Reactive Dual-arm Manipulation)

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Abstract

Research findings on Robotics are discussed in a new report. According to news reporting originating from Hannover, Germany, by NewsRx correspondents, research stated, “Future robots operating in fast-changing anthropomorphic environments need to be reactive, safe, flexible, and intuitively use both arms (comparable to humans) to handle task-space constrained manipulation scenarios. Furthermore, dynamic environments pose additional challenges for motion planning due to a continual requirement for validation and refinement of plans.” Financial support for this research came from State of Bavaria for the Geriatronics project. Our news editors obtained a quote from the research from Leibniz University Hannover, “This work addresses the issues with vector-field-based motion generation strategies, which are often prone to localminima problems. We aim to bridge the gap between reactive solutions, global planning, and constrained cooperative (two-arm) manipulation in partially known surroundings. To this end, we introduce novel planning and real-time control strategies leveraging the geometry of the task space that are inherently coupled for seamless operation in dynamic scenarios. Our integrated multiagent global planning and control scheme explores controllable sets in the previously introduced cooperative dual task space and flexibly controls them by exploiting the redundancy of the high degree-of-freedom (DOF) system. The planning and control framework is extensively validated in complex, cluttered, and nonstationary simulation scenarios where our framework is able to complete constrained tasks in a reliable manner, whereas existing solutions fail. We also perform additional real-world experiments with a two-armed 14 DOF torque-controlled KoBo robot.”

Key words

Hannover/Germany/Europe/Emerging Technologies/Machine Learning/Nano-robot/Robotics/Leibniz University Hannover

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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