Learning and Composing Primitive Skills for Dual-Arm Manipulation
| Autor: | Yvan Petillot, Michael Mistry, Paola Ardón, Èric Pairet |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Computer science business.industry Primitive skills Autonomous agent Robotics 02 engineering and technology DUAL (cognitive architecture) Modularity 03 medical and health sciences 020901 industrial engineering & automation 0302 clinical medicine Human–computer interaction Robot Artificial intelligence business 030217 neurology & neurosurgery iCub Humanoid robot |
| Zdroj: | Towards Autonomous Robotic Systems ISBN: 9783030238063 TAROS (1) |
| DOI: | 10.1007/978-3-030-23807-0_6 |
| Popis: | In an attempt to confer robots with complex manipulation capabilities, dual-arm anthropomorphic systems have become an important research topic in the robotics community. Most approaches in the literature rely upon a great understanding of the dynamics underlying the system’s behaviour and yet offer limited autonomous generalisation capabilities. To address these limitations, this work proposes a modelisation for dual-arm manipulators based on dynamic movement primitives laying in two orthogonal spaces. The modularity and learning capabilities of this model are leveraged to formulate a novel end-to-end learning-based framework which (i) learns a library of primitive skills from human demonstrations, and (ii) composes such knowledge simultaneously and sequentially to confront novel scenarios. The feasibility of the proposal is evaluated by teaching the iCub humanoid the basic skills to succeed on simulated dual-arm pick-and-place tasks. The results suggest the learning and generalisation capabilities of the proposed framework extend to autonomously conduct undemonstrated dual-arm manipulation tasks. |
| Databáze: | OpenAIRE |
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