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A vision-language-guided and deep reinforcement learning-enabled approach for unstructured human-robot collaborative manufacturing task fulfilment

Pai Zheng, Chengxi Li, Junming Fan, Lihui Wang

Year
2024
Citations
50

Abstract

Human-Robot Collaboration (HRC) has emerged as a pivot in contemporary human-centric smart manufacturing scenarios. However, the fulfilment of HRC tasks in unstructured scenes brings many challenges to be overcome. In this work, mixed reality head-mounted display is modelled as an effective data collection, communication, and state representation interface/tool for HRC task settings. By integrating vision-language cues with large language model, a vision-language-guided HRC task planning approach is firstly proposed. Then, a deep reinforcement learning-enabled mobile manipulator motion control policy is generated to fulfil HRC task primitives. Its feasibility is demonstrated in several HRC unstructured manufacturing tasks with comparative results.

Keywords

Reinforcement learningTask (project management)Computer scienceHuman–computer interactionArtificial intelligenceInterface (matter)Representation (politics)RobotTask analysisEngineering

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