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- 01H6ZPY959S3149PX41EM6WW9S classification P1.
- 01H6ZPY959S3149PX41EM6WW9S date "2023".
- 01H6ZPY959S3149PX41EM6WW9S language "eng".
- 01H6ZPY959S3149PX41EM6WW9S type conference.
- 01H6ZPY959S3149PX41EM6WW9S hasPart 01H9RH8KA3JWC0SGTNBD9Z5FQV.pdf.
- 01H6ZPY959S3149PX41EM6WW9S subject "Technology and Engineering".
- 01H6ZPY959S3149PX41EM6WW9S doi "10.1109/aim46323.2023.10196273".
- 01H6ZPY959S3149PX41EM6WW9S isbn "9781665476331".
- 01H6ZPY959S3149PX41EM6WW9S issn "2159-6255".
- 01H6ZPY959S3149PX41EM6WW9S presentedAt urn:uuid:6ec3762a-b3a0-4e38-bb6d-751ab170bb67.
- 01H6ZPY959S3149PX41EM6WW9S abstract "We introduce a framework for cooperative manipulation, applied on an underactuated manipulation problem. Two stationary robotic manipulators are required to cooperate in order to reposition an object within their shared work space. Control of multi-agent systems for manipulation tasks cannot rely on individual control strategies with little to no communication between the agents that serve the common objective through swarming. Instead a coordination strategy is required that queries subtasks to the individual agents. We formulate the problem in a Task And Motion Planning (TAMP) setting, while considering a decomposition strategy that allows us to treat the task and motion planning problems separately. We solve the supervisory planning problem offline using deep Reinforcement Learning techniques resulting into a supervisory policy capable of coordinating the two manipulators into a successful execution of the pick-and-place task. Additionally, a benefit of solving the task planning problem offline is the possibility of real-time (re)planning, demonstrating robustness in the event of subtask execution failure or on-the-fly task changes. The framework achieved zero-shot deployment on the real setup with a success rate that is higher than 90%.".
- 01H6ZPY959S3149PX41EM6WW9S author 0C481C22-7F7E-11E6-8766-2C13B5D1D7B1.
- 01H6ZPY959S3149PX41EM6WW9S author 2DFB9CC2-F0EE-11E1-A9DE-61C894A0A6B4.
- 01H6ZPY959S3149PX41EM6WW9S author 936D1328-6FC6-11E6-B34B-B74CB5D1D7B1.
- 01H6ZPY959S3149PX41EM6WW9S author F7378570-F0ED-11E1-A9DE-61C894A0A6B4.
- 01H6ZPY959S3149PX41EM6WW9S dateCreated "2023-08-04T07:24:39Z".
- 01H6ZPY959S3149PX41EM6WW9S dateModified "2024-10-29T18:45:35Z".
- 01H6ZPY959S3149PX41EM6WW9S name "A supervisory learning control framework for autonomous & real-time task planning for an underactuated cooperative robotic task".
- 01H6ZPY959S3149PX41EM6WW9S pagination urn:uuid:ad20a3bf-80a6-45de-9588-0ecc3ab3c8c4.
- 01H6ZPY959S3149PX41EM6WW9S publisher urn:uuid:1f42717f-8bfc-46e3-8afe-8cdafcf51d1b.
- 01H6ZPY959S3149PX41EM6WW9S sameAs LU-01H6ZPY959S3149PX41EM6WW9S.
- 01H6ZPY959S3149PX41EM6WW9S sourceOrganization urn:uuid:3bb39e17-1658-4fe7-bcec-39705965a32f.
- 01H6ZPY959S3149PX41EM6WW9S sourceOrganization urn:uuid:42e96e05-3097-4b65-870f-fbfe089b4c96.
- 01H6ZPY959S3149PX41EM6WW9S type P1.