TY - GEN
T1 - A Review of Classical and Learning Based Approaches in Task and Motion Planning
AU - Zhang, Kai
AU - Lucet, Eric
AU - Sandretto, Julien Alexandre Dit
AU - Kchir, Selma
AU - Filliat, David
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - Robots are widely used in many tedious and simple works. But, with the advance of technology, they are expected to work in more complex environments and participate in more challenging tasks. Correspondingly, more intelligent and robust algorithms are required. As a domain having been explored for decades, task and motion planning (TAMP) methods have been applied in various applications and have achieved important results, while still being developed, particularly through the integration of more machine learning approaches. This paper summarizes the development of TAMP, presenting its background, popular methods, application environment, and limitations. In particularly, it compares different simulation environments and points out their advantages and disadvantages. Besides, the existing methods are categorized by their contribution and applications, intending to draw a clear picture for beginners.
AB - Robots are widely used in many tedious and simple works. But, with the advance of technology, they are expected to work in more complex environments and participate in more challenging tasks. Correspondingly, more intelligent and robust algorithms are required. As a domain having been explored for decades, task and motion planning (TAMP) methods have been applied in various applications and have achieved important results, while still being developed, particularly through the integration of more machine learning approaches. This paper summarizes the development of TAMP, presenting its background, popular methods, application environment, and limitations. In particularly, it compares different simulation environments and points out their advantages and disadvantages. Besides, the existing methods are categorized by their contribution and applications, intending to draw a clear picture for beginners.
KW - Review
KW - Simulation environment
KW - Task and motion planning
U2 - 10.1007/978-3-031-48303-5_5
DO - 10.1007/978-3-031-48303-5_5
M3 - Conference contribution
AN - SCOPUS:85180156801
SN - 9783031483028
T3 - Lecture Notes in Networks and Systems
SP - 83
EP - 99
BT - Informatics in Control, Automation and Robotics - 19th International Conference, ICINCO 2022, Revised Selected Papers
A2 - Gini, Giuseppina
A2 - Nijmeijer, Henk
A2 - Burgard, Wolfram
A2 - Filev, Dimitar
PB - Springer Science and Business Media Deutschland GmbH
T2 - 19th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2022
Y2 - 14 July 2022 through 16 July 2022
ER -