Learned Stochastic Mobility Prediction for Planning with Control Uncertainty on Unstructured Terrain-Reference-Cited by-同舟云学术

Learned Stochastic Mobility Prediction for Planning with Control Uncertainty on Unstructured Terrain

Published:2014-09-09 Issue:6 Volume:31 Page:969-995
ISSN:1556-4959
Container-title:Journal of Field Robotics
language:en
Short-container-title:J. Field Robotics

Author:

Peynot Thierry¹,Lui Sin-Ting²,McAllister Rowan³,Fitch Robert²,Sukkarieh Salah²

Affiliation:

1. School of Electrical Engineering and Computer Science; Queensland University of Technology; Brisbane QLD 4001 Australia

2. Australian Centre for Field Robotics; The University of Sydney; NSW 2006 Australia

3. Department of Engineering; University of Cambridge; Cambridge CB2 1PZ United Kingdom

Funder

Australian Government's DIISR grant “Australian Space Research Program,”

Australian Centre for Field Robotics

New South Wales State Government

Air Force Research Laboratory

Publisher

Wiley

Subject

Computer Science Applications,Control and Systems Engineering

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/rob.21536/fullpdf

Reference47 articles.

1. Alterovitz , R. Simeon , T. Goldberg , K. 2007 The stochastic motion roadmap: A sampling framework for planning with Markov motion uncertainty Robotics: Science and Systems III 233 240

2. Learning and prediction of slip from visual information;Angelova;Journal of Field Robotics,2007

3. Berb , J. Abbeel , P. Goldberg , K. 2010 LQG-MP: Optimized path planning for robots with motion uncertainty and imperfect state information Robotics: Science and Systems VI 129 136

4. Resilient machines through continuous self-modeling;Bongard;Science,2006

Cited by 24 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. An embarrassingly simple approach for visual navigation of forest environments;Frontiers in Robotics and AI;2023-06-28

2. End-to-End Learning for Visual Navigation of Forest Environments;Forests;2023-01-31

3. A MDPs-Based Dynamic Path Planning in Unknown Environments for Hopping Locomotion;IEEE Access;2023

4. Hopping path planning in uncertain environments for planetary explorations;ROBOMECH Journal;2022-02-14

5. A New Path Planning Architecture to Consider Motion Uncertainty in Natural Environment;2020 IEEE International Conference on Robotics and Automation (ICRA);2020-05