A Simple Approach to Constraint-Aware Imitation Learning with Application to Autonomous Racing
On the map: Offline RL and imitation learning from data → Imitation learning methods
Abstract (arXiv)
Guaranteeing constraint satisfaction is challenging in imitation learning (IL), particularly in tasks that require operating near a system's handling limits. Traditional IL methods, such as Behavior Cloning (BC), often struggle to enforce constraints, leading to suboptimal performance in high-precision tasks. In this paper, we present a simple approach to incorporating safety into the IL objective. Through simulations, we empirically validate our approach on an autonomous racing task with both full-state and image feedback, demonstrating improved constraint satisfaction and greater consistency in task performance compared to BC.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in Imitation learning methods, one of 13 directions in Offline RL and imitation learning from data. Builds on 20 of its 28 references that are in the map. First posted on arXiv 10 Mar 2025.
Builds on
20 of 28 references.
Closest ancestors · 4
Same direction, newest first
- 2023A Survey of Imitation Learning: Algorithms, Recent Developments, and Challenges5 Sep
- 2022Interactive Imitation Learning in Robotics: A Survey31 Oct
- 2021Feedback in Imitation Learning: The Three Regimes of Covariate Shift4 Feb
- 2018Truncated Horizon Policy Search: Combining Reinforcement Learning & Imitation Learning29 May
Other references · 16
- 2017CARLA: An Open Urban Driving Simulatorcited by 2,431
- 2016End to End Learning for Self-Driving Carscited by 1,000
- 2019Control Barrier Functions: Theory and Applicationscited by 332
- 2017Hamilton-Jacobi Reachability: A Brief Overview and Recent Advancescited by 186
- 2018A predictive safety filter for learning-based control of constrained nonlinear dynamical systemscited by 91
- 2016Query-Efficient Imitation Learning for End-to-End Autonomous Drivingcited by 83
- 2020Deep Drone Acrobaticscited by 66
- 2022Autonomous Vehicles on the Edge: A Survey on Autonomous Vehicle Racingcited by 56
- 2017Optimization-Based Autonomous Racing of 1:43 Scale RC Carscited by 47
- 2016Learning Model Predictive Control for iterative tasks. A Data-Driven Control Frameworkcited by 38
- 2018Linear model predictive safety certification for learning-based controlcited by 34
- 2024SAFE-GIL: SAFEty Guided Imitation Learning for Robotic Systemscited by 13
4 more
- 2022End-to-End Imitation Learning with Safety Guarantees using Control Barrier Functionscited by 10
- 2020Understanding Multi-Modal Perception Using Behavioral Cloning for Peg-In-a-Hole Insertion Taskscited by 8
- 2024Safety Filters for Black-Box Dynamical Systems by Learning Discriminating Hyperplanescited by 8
- 2024Learning Ensembles of Vision-based Safety Control Filterscited by 2
Built on by
Citing papers per year: 2025: 2.
2 papers.
Similar, not cited
Close in wording, no citation either way
- 2026Interleaved Projected Gradient Descent for Safe Imitation Learning
- 2022Differentiable Constrained Imitation Learning for Robot Motion Planning and Control
- 2026Difference-Aware Retrieval Policies for Imitation Learning
- 2026Infeasible optimization problems and the hierarchical augmented Lagrangian method in imitation learning
- 2021Imitation Learning: Progress, Taxonomies and Challenges
- 2019A Linearly Constrained Nonparametric Framework for Imitation Learning
- 2025A Smooth Sea Never Made a Skilled SAILOR: Robust Imitation via Learning to Search
- 2026It's Not Just More Demos: Counterfactual Action Sensitivity Coverage for Data-Efficient Robust Robot Imitation