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Learning-based Robust Motion Planning with Guaranteed Stability: A
  Contraction Theory Approach

Learning-based Robust Motion Planning with Guaranteed Stability: A Contraction Theory Approach

25 February 2021
Hiroyasu Tsukamoto
Soon-Jo Chung
    OOD
ArXivPDFHTML

Papers citing "Learning-based Robust Motion Planning with Guaranteed Stability: A Contraction Theory Approach"

5 / 5 papers shown
Title
CaRT: Certified Safety and Robust Tracking in Learning-based Motion
  Planning for Multi-Agent Systems
CaRT: Certified Safety and Robust Tracking in Learning-based Motion Planning for Multi-Agent Systems
Hiroyasu Tsukamoto
Benjamin Rivière
Changrak Choi
A. Rahmani
Soon-Jo Chung
13
0
0
13 Jul 2023
Safe Output Feedback Motion Planning from Images via Learned Perception
  Modules and Contraction Theory
Safe Output Feedback Motion Planning from Images via Learned Perception Modules and Contraction Theory
Glen Chou
N. Ozay
Dmitry Berenson
19
22
0
14 Jun 2022
Learning Contraction Policies from Offline Data
Learning Contraction Policies from Offline Data
Navid Rezazadeh
Maxwell Kolarich
Solmaz S. Kia
Negar Mehr
OffRL
18
7
0
11 Dec 2021
Demonstration-Efficient Guided Policy Search via Imitation of Robust
  Tube MPC
Demonstration-Efficient Guided Policy Search via Imitation of Robust Tube MPC
Andrea Tagliabue
Dong-Ki Kim
M. Everett
Jonathan P. How
56
22
0
21 Sep 2021
Motion Planning Among Dynamic, Decision-Making Agents with Deep
  Reinforcement Learning
Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning
Michael Everett
Yu Fan Chen
Jonathan P. How
146
509
0
04 May 2018
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