TY - GEN
T1 - Learning and Composing Primitive Skills for Dual-Arm Manipulation
AU - Pairet, Èric
AU - Ardón, Paola
AU - Mistry, Michael
AU - Petillot, Yvan
PY - 2019/6/28
Y1 - 2019/6/28
N2 - 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.
AB - 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.
KW - Autonomous agents
KW - Dual arm manipulation
KW - Humanoid robots
KW - Learning from demonstration
KW - Model learning for control
UR - http://www.scopus.com/inward/record.url?scp=85068992840&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-23807-0_6
DO - 10.1007/978-3-030-23807-0_6
M3 - Conference contribution
AN - SCOPUS:85068992840
SN - 9783030238063
T3 - Lecture Notes in Computer Science
SP - 65
EP - 77
BT - Towards Autonomous Robotic Systems
A2 - Althoefer, Kaspar
A2 - Konstantinova, Jelizaveta
A2 - Zhang, Ketao
PB - Springer
T2 - 20th Towards Autonomous Robotic Systems Conference 2019
Y2 - 3 July 2019 through 5 July 2019
ER -