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Dynamic control of soft robotic manipulators is an open problem yet to be well explored and analyzed. Most of the current applications of soft robotic manipulators utilize static or quasi-dynamic controllers based on kinematic models or linearity in the joint space. However, such approaches are not truly exploiting the rich dynamics of a soft-bodied system. In this paper, we present a model-based policy learning algorithm for closed-loop predictive control of a soft robotic manipulator. The forward dynamic model is represented using a recurrent neural network. The closed-loop policy is derived using trajectory optimization and supervised learning. The approach is verified first on a simulated piecewise constant strain model of a cable driven under-actuated soft manipulator. Furthermore, we experimentally demonstrate on a soft pneumatically actuated manipulator how closed-loop control policies can be derived that can accommodate variable frequency control and unmodeled external loads.
", "publication_date": "2018-11-12", "publisher": "Zenodo", "resource_type": { "id": "publication-article", "title": { "de": "Zeitschriftenartikel", "en": "Journal article" } }, "rights": [ { "description": { "en": "The Creative Commons Attribution license allows re-distribution and re-use of a licensed work on the condition that the creator is appropriately credited." }, "icon": "cc-by-icon", "id": "cc-by-4.0", "props": { "scheme": "spdx", "url": "https://creativecommons.org/licenses/by/4.0/legalcode" }, "title": { "en": "Creative Commons Attribution 4.0 International" } } ], "title": "Model-Based Reinforcement Learning for Closed-Loop Dynamic Control of Soft Robotic Manipulators" }, "parent": { "access": { "owned_by": { "user": 83206 } }, "communities": {}, "id": "3759635", "pids": {} }, "pids": { "doi": { "identifier": "10.1109/TRO.2018.2878318", "provider": "external" }, "oai": { "identifier": "oai:zenodo.org:3759636", "provider": "oai" } }, "revision_id": 2, "stats": { "all_versions": { "data_volume": 3050815515.0, "downloads": 877, "unique_downloads": 847, "unique_views": 113, "views": 131 }, "this_version": { "data_volume": 3022985955.0, "downloads": 869, "unique_downloads": 839, "unique_views": 113, "views": 131 } }, "status": "published", "updated": "2020-04-21T20:20:18.001265+00:00", "versions": { "index": 1, "is_latest": true } }