# Experimental investigation of pose informed reinforcement learning for skid-steered visual navigation

arXiv: https://arxiv.org/abs/2506.21732 · HTML: https://mlsanity.com/paper/2506.21732/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Placed in RL for autonomous driving and traffic, one of 15 directions in Deep reinforcement learning methods.
- Builds on 14 of its 77 references that are in the map.
- First posted on arXiv 26 Jun 2025.

## Placed in

- Deep reinforcement learning methods / [RL for autonomous driving and traffic](https://mlsanity.com/deeprl/rl-for-autonomous-driving-and-traffic/)

## Builds on (most cited first, 14 of 14)

- [End to End Learning for Self-Driving Cars](https://mlsanity.com/paper/1604.07316/) (2016)
- [Sim-to-Real Transfer in Deep Reinforcement Learning for Robotics: a Survey](https://mlsanity.com/paper/2009.13303/) (2020)
- [End-to-End Model-Free Reinforcement Learning for Urban Driving using Implicit Affordances](https://mlsanity.com/paper/1911.10868/) (2019)
- [CIRL: Controllable Imitative Reinforcement Learning for Vision-based Self-driving](https://mlsanity.com/paper/1807.03776/) (2018)
- [End-to-End Race Driving with Deep Reinforcement Learning](https://mlsanity.com/paper/1807.02371/) (2018)
- [RoadRunner -- Learning Traversability Estimation for Autonomous Off-road Driving](https://mlsanity.com/paper/2402.19341/) (2024)
- [Regulated Pure Pursuit for Robot Path Tracking](https://mlsanity.com/paper/2305.20026/) (2023)
- [Evaluation of Skid-Steering Kinematic Models for Subarctic Environments](https://mlsanity.com/paper/2004.05131/) (2020)
- [Vision-based DRL Autonomous Driving Agent with Sim2Real Transfer](https://mlsanity.com/paper/2305.11589/) (2023)
- [Online identification of skidding modes with interactive multiple model estimation](https://mlsanity.com/paper/2409.20554/) (2024)
- [Dynamic Modeling and Simulation of a Four-wheel Skid-Steer Mobile Robot using Linear Graphs](https://mlsanity.com/paper/2110.00323/) (2021)
- [A Probabilistic Motion Model for Skid-Steer Wheeled Mobile Robot Navigation on Off-Road Terrains](https://mlsanity.com/paper/2402.18065/) (2024)
- [Stabilization of vertical motion of a vehicle on bumpy terrain using deep reinforcement learning](https://mlsanity.com/paper/2409.14207/) (2024)
- [Characterizing gaussian mixture of motion modes for skid-steer vehicle state estimation](https://mlsanity.com/paper/2505.00200/) (2025)

## Abstract (arXiv)

Vision-based lane keeping is a topic of significant interest in the robotics and autonomous ground vehicles communities in various on-road and off-road applications. The skid-steered vehicle architecture has served as a useful vehicle platform for human controlled operations. However, systematic modeling, especially of the skid-slip wheel terrain interactions (primarily in off-road settings) has created bottlenecks for automation deployment. End-to-end learning based methods such as imitation learning and deep reinforcement learning, have gained prominence as a viable deployment option to counter the lack of accurate analytical models. However, the systematic formulation and subsequent verification/validation in dynamic operation regimes (particularly for skid-steered vehicles) remains a work in progress. To this end, a novel approach for structured formulation for learning visual navigation is proposed and investigated in this work. Extensive software simulations, hardware evaluations and ablation studies now highlight the significantly improved performance of the proposed approach against contemporary literature.