mlsanityData to 14 Oct 2026

VI-IKD: High-Speed Accurate Off-Road Navigation using Learned Visual-Inertial Inverse Kinodynamics

arXiv 2203.15983 ↗First posted 30 Mar 2022cs.RO cs.AI cs.CVcited by 21

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Abstract (arXiv)

One of the key challenges in high speed off road navigation on ground vehicles is that the kinodynamics of the vehicle terrain interaction can differ dramatically depending on the terrain. Previous approaches to addressing this challenge have considered learning an inverse kinodynamics (IKD) model, conditioned on inertial information of the vehicle to sense the kinodynamic interactions. In this paper, we hypothesize that to enable accurate high-speed off-road navigation using a learned IKD model, in addition to inertial information from the past, one must also anticipate the kinodynamic interactions of the vehicle with the terrain in the future. To this end, we introduce Visual-Inertial Inverse Kinodynamics (VI-IKD), a novel learning based IKD model that is conditioned on visual information from a terrain patch ahead of the robot in addition to past inertial information, enabling it to anticipate kinodynamic interactions in the future. We validate the effectiveness of VI-IKD in accurate high-speed off-road navigation experimentally on a scale 1/5 UT-AlphaTruck off-road autonomous vehicle in both indoor and outdoor environments and show that compared to other state-of-the-art approaches, VI-IKD enables more accurate and robust off-road navigation on a variety of different terrains at speeds of up to 3.5 m/s.

Key facts. Cited by 21 papers in the map (data through 14 Oct 2026). Builds on 15 of its 35 references that are in the map. First posted on arXiv 30 Mar 2022.

Builds on

15 of 35 references.

References · 15

  1. 2016End to End Learning for Self-Driving Carscited by 1,009
  2. 2022Learning robust perceptive locomotion for quadrupedal robots in the wildcited by 382
  3. 2022Socially Compliant Navigation Dataset (SCAND): A Large-Scale Dataset of Demonstrations for Social Navigationcited by 127
  4. 2016Decentralized Non-communicating Multiagent Collision Avoidance with Deep Reinforcement Learningcited by 118
  5. 2017Virtual-to-real Deep Reinforcement Learning: Continuous Control of Mobile Robots for Mapless Navigationcited by 98
  6. 2018Learning Navigation Behaviors End-to-End with AutoRLcited by 70
  7. 2016From Perception to Decision: A Data-driven Approach to End-to-end Motion Planning for Autonomous Ground Robotscited by 44
  8. 2021VOILA: Visual-Observation-Only Imitation Learning for Autonomous Navigationcited by 31
  9. 2021Learning Inverse Kinodynamics for Accurate High-Speed Off-Road Navigation on Unstructured Terraincited by 25
  10. 2020Stochastic Grounded Action Transformation for Robot Learning in Simulationcited by 16
  11. 2020Toward Agile Maneuvers in Highly Constrained Spaces: Learning from Hallucinationcited by 11
  12. 2020Learning to Drive Off Road on Smooth Terrain in Unstructured Environments Using an On-Board Camera and Sparse Aerial Imagescited by 9
3 more
  1. 2021From Agile Ground to Aerial Navigation: Learning from Learned Hallucinationcited by 9
  2. 2018Vision-Based High Speed Driving with a Deep Dynamic Observercited by 7
  3. 2020Agile Robot Navigation through Hallucinated Learning and Sober Deploymentcited by 7

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 3; 2023: 6; 2024: 9; 2025: 2; 2026: 1.

21 papers.

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  1. 2022Learning Model Predictive Controllers with Real-Time Attention for Real-World Navigationcited by 29
  2. 2024RoadRunner -- Learning Traversability Estimation for Autonomous Off-road Drivingcited by 26
  3. 2024DTG : Diffusion-based Trajectory Generation for Mapless Global Navigationcited by 13
  4. 2022High-Speed Accurate Robot Control using Learned Forward Kinodynamics and Non-linear Least Squares Optimizationcited by 11
  5. 2023STERLING: Self-Supervised Terrain Representation Learning from Unconstrained Robot Experiencecited by 11
  6. 2022VINet: Visual and Inertial-based Terrain Classification and Adaptive Navigation over Unknown Terraincited by 8
  7. 2023Learning Terrain-Aware Kinodynamic Model for Autonomous Off-Road Rally Driving With Model Predictive Path Integral Controlcited by 8
  8. 2023Bridging Active Exploration and Uncertainty-Aware Deployment Using Probabilistic Ensemble Neural Network Dynamicscited by 7
  9. 2023Wait, That Feels Familiar: Learning to Extrapolate Human Preferences for Preference Aligned Path Planningcited by 7
  10. 2024Reinforcement Learning for Wheeled Mobility on Vertically Challenging Terraincited by 7
  11. 2023SOCIALGYM 2.0: Simulator for Multi-Agent Social Robot Navigation in Shared Human Spacescited by 5
  12. 2024VANP: Learning Where to See for Navigation with Self-Supervised Vision-Action Pre-Trainingcited by 5
9 more
  1. 2024Grounded Curriculum Learningcited by 5
  2. 2023A Study on Learning Social Robot Navigation with Multimodal Perceptioncited by 4
  3. 2024VertiSelector: Automatic Curriculum Learning for Wheeled Mobility on Vertically Challenging Terraincited by 3
  4. 2025GACL: Grounded Adaptive Curriculum Learning with Active Task and Performance Monitoringcited by 3
  5. 2024WROOM: An Autonomous Driving Approach for Off-Road Navigationcited by 2
  6. 2025T-CBF: Traversability-based Control Barrier Function to Navigate Vertically Challenging Terraincited by 2
  7. 2024Dyna-LfLH: Learning Agile Navigation in Dynamic Environments from Learned Hallucinationcited by 1
  8. 2024Aligning Robot Navigation Behaviors with Human Intentions and Preferencescited by 0
  9. 2026Adapting Generalist Vehicle Models for High-Speed MPC Across Terrainscited by 0