survey

Recent Trends in Task and Motion Planning for Robotics: A Survey

Authors:

Kenli LiAuthors Info & Claims

ACM Computing Surveys, Volume 55, Issue 13s

Article No.: 289, Pages 1 - 36

https://doi.org/10.1145/3583136

Published: 13 July 2023 Publication History

Abstract

Autonomous robots are increasingly served in real-world unstructured human environments with complex long-horizon tasks, such as restaurant serving and office delivery. Task and motion planning (TAMP) is a recent research method in Artificial Intelligence Planning for these applications. TAMP integrates high-level abstract reasoning with the low-level geometric feasibility check and thus is more comprehensive than traditional task planning methods. While regular TAMP approaches are challenged by different types of uncertainties and the generalization of various applications when implemented in real-world scenarios. This article systematically reviews the most relevant approaches to TAMP and classifies them according to their features and emphasis; it categorizes the challenges and presents online TAMP and machine learning-based TAMP approaches for addressing them.

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Index Terms

Recent Trends in Task and Motion Planning for Robotics: A Survey
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
    2. Planning and scheduling
      1. Planning under uncertainty
      2. Robotic planning
  2. Machine learning
2. General and reference
  1. Document types
    1. Surveys and overviews

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 55, Issue 13s

December 2023

1367 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3606252

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Published: 13 July 2023

Online AM: 07 February 2023

Accepted: 30 January 2023

Revised: 22 January 2023

Received: 14 August 2022

Published in CSUR Volume 55, Issue 13s

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https://doi.org/10.1016/j.rcim.2024.102925
Mansouri MStreet CWarsame Y(2025)The CONVINCE Perspective on Task and Motion Planning in Dynamic EnvironmentsEuropean Robotics Forum 202410.1007/978-3-031-76428-8_39(206-210)Online publication date: 1-Jan-2025
https://doi.org/10.1007/978-3-031-76428-8_39
Byeon SOh Y(2024)Task Planning Algorithm with Graph-based State RepresentationJournal of Korea Robotics Society10.7746/jkros.2024.19.2.19619:2(196-202)Online publication date: 31-May-2024
https://doi.org/10.7746/jkros.2024.19.2.196
Anwar Ali Z(2024)Introductory Chapter: MOTION PLANNING FOR DYNAMIC AGENTSMotion Planning for Dynamic Agents10.5772/intechopen.1003898Online publication date: 17-Jan-2024
https://doi.org/10.5772/intechopen.1003898
Jeon JJung HPico NLuong TMoon H(2024)Task-Motion Planning System for Socially Viable Service Robots Based on Object ManipulationBiomimetics10.3390/biomimetics90704369:7(436)Online publication date: 17-Jul-2024
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Hellander ABergman KAxehill D(2024) Improved Task and Motion Planning for Rearrangement Problems using Optimal Control * 2024 IEEE Intelligent Vehicles Symposium (IV)10.1109/IV55156.2024.10588789(2033-2040)Online publication date: 2-Jun-2024
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Bedkowski JMajek KPelka M(2024)Semi Autonomous Mobile Robot for Inspection Missions2024 IEEE 12th International Conference on Intelligent Systems (IS)10.1109/IS61756.2024.10705242(1-4)Online publication date: 29-Aug-2024
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Izzo RBardaro GMatteucci M(2024)BTGenBot: Behavior Tree Generation for Robotic Tasks with Lightweight LLMs2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS58592.2024.10802304(9684-9690)Online publication date: 14-Oct-2024
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Jaitly AFarzan S(2024)PAAMP: Polytopic Action-Set And Motion Planning for Long Horizon Dynamic Motion Planning via Mixed Integer Linear Programming2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS58592.2024.10802176(7617-7624)Online publication date: 14-Oct-2024
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Watanabe KFainekos GHoxha BLahijanian MOkamoto HSankaranarayanan S(2024)Optimal Planning for Timed Partial Order Specifications2024 IEEE International Conference on Robotics and Automation (ICRA)10.1109/ICRA57147.2024.10611547(17093-17099)Online publication date: 13-May-2024
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