mlsanityData to 14 Oct 2026

Self-Reflective Terrain-Aware Robot Adaptation for Consistent Off-Road Ground Navigation

arXiv 2111.06742 ↗First posted 12 Nov 2021cs.RO cs.LGcited by 1

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Abstract (arXiv)

Ground robots require the crucial capability of traversing unstructured and unprepared terrains and avoiding obstacles to complete tasks in real-world robotics applications such as disaster response. When a robot operates in off-road field environments such as forests, the robot's actual behaviors often do not match its expected or planned behaviors, due to changes in the characteristics of terrains and the robot itself. Therefore, the capability of robot adaptation for consistent behavior generation is essential for maneuverability on unstructured off-road terrains. In order to address the challenge, we propose a novel method of self-reflective terrain-aware adaptation for ground robots to generate consistent controls to navigate over unstructured off-road terrains, which enables robots to more accurately execute the expected behaviors through robot self-reflection while adapting to varying unstructured terrains. To evaluate our method's performance, we conduct extensive experiments using real ground robots with various functionality changes over diverse unstructured off-road terrains. The comprehensive experimental results have shown that our self-reflective terrain-aware adaptation method enables ground robots to generate consistent navigational behaviors and outperforms the compared previous and baseline techniques.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 22 of its 136 references that are in the map. First posted on arXiv 12 Nov 2021.

Builds on

22 of 136 references.

References · 22

  1. 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,859
  2. 2021Convex optimizationcited by 2,515
  3. 2021RMA: Rapid Motor Adaptation for Legged Robotscited by 508
  4. 2020RELLIS-3D Dataset: Data, Benchmarks and Analysiscited by 119
  5. 2020BADGR: An Autonomous Self-Supervised Learning-Based Navigation Systemcited by 102
  6. 2017Self-supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot Navigationcited by 77
  7. 2016Generalizing Koopman Theory to allow for inputs and controlcited by 53
  8. 2017Introduction to Tensor Decompositions and their Applications in Machine Learningcited by 46
  9. 2019Efficient Iterative Linear-Quadratic Approximations for Nonlinear Multi-Player General-Sum Differential Gamescited by 37
  10. 2020Bi-directional Domain Adaptation for Sim2Real Transfer of Embodied Navigation Agentscited by 35
  11. 2020APPLI: Adaptive Planner Parameter Learning From Interventionscited by 19
  12. 2017Human-Robot Mutual Adaptation in Shared Autonomycited by 16
10 more
  1. 2019Mapless Navigation among Dynamics with Social-safety-awareness: a reinforcement learning approach from 2D laser scanscited by 10
  2. 2018Adaptive Model Predictive Control for High-Accuracy Trajectory Tracking in Changing Conditionscited by 7
  3. 2019Modeling, Identification and Control of Model Jet Engines for Jet Powered Roboticscited by 5
  4. 2018NimbRo Rescue: Solving Disaster-Response Tasks through Mobile Manipulation Robot Momarocited by 3
  5. 2020Constrained Differential Dynamic Programming Revisitedcited by 3
  6. 2020An Iterative LQR Controller for Off-Road and On-Road Vehicles using a Neural Network Dynamics Modelcited by 3
  7. 2020Uncertainty-Constrained Differential Dynamic Programming in Belief Space for Vision Based Robotscited by 3
  8. 2017On orthogonal tensors and best rank-one approximation ratiocited by 2
  9. 2020Adaptive Robot Navigation with Collision Avoidance subject to 2nd-order Uncertain Dynamicscited by 2
  10. 2017Sequence-based Multimodal Apprenticeship Learning For Robot Perception and Decision Makingcited by 1

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