Recursively Feasible Shrinking-Horizon MPC in Dynamic Environments with Conformal Prediction Guarantees
Abstract: In this paper, we focus on the problem of shrinking-horizon Model Predictive Control (MPC) in uncertain dynamic environments. We consider controlling a deterministic autonomous system that interacts with uncontrollable stochastic agents during its mission. Employing tools from conformal prediction, existing works derive high-confidence prediction regions for the unknown agent trajectories, and integrate these regions in the design of suitable safety constraints for MPC. Despite guaranteeing probabilistic safety of the closed-loop trajectories, these constraints do not ensure feasibility of the respective MPC schemes for the entire duration of the mission. We propose a shrinking-horizon MPC that guarantees recursive feasibility via a gradual relaxation of the safety constraints as new prediction regions become available online. This relaxation enforces the safety constraints to hold over the least restrictive prediction region from the set of all available prediction regions. In a comparative case study with the state of the art, we empirically show that our approach results in tighter prediction regions and verify recursive feasibility of our MPC scheme.
- Social lstm: Human trajectory prediction in crowded spaces. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 961–971, 2016.
- Neural predictive monitoring. In Runtime Verification: 19th International Conference, RV 2019, Porto, Portugal, October 8–11, 2019, Proceedings 19, pages 129–147. Springer, 2019.
- Reactive motion planning with probabilisticsafety guarantees. In Conference on Robot Learning, pages 1958–1970. PMLR, 2021.
- Adaptive conformal prediction for motion planning among dynamic agents. In Learning for Dynamics and Control Conference, pages 300–314. PMLR, 2023.
- Robot motion planning in dynamic, uncertain environments. IEEE Transactions on Robotics, 28(1):101–115, 2011a.
- Probabilistic collision checking with chance constraints. IEEE Transactions on Robotics, 27(4):809–815, 2011b.
- Statistical verification of autonomous systems using surrogate models and conformal inference. arXiv preprint arXiv:2004.00279, 2020.
- Probabilistically safe robot planning with confidence-based human predictions. arXiv preprint arXiv:1806.00109, 2018.
- Confidence-aware motion prediction for real-time collision avoidance1. The International Journal of Robotics Research, 39(2-3):250–265, 2020.
- Human trajectory forecasting in crowds: A deep learning perspective. IEEE Transactions on Intelligent Transportation Systems, 23(7):7386–7400, 2021.
- Feature-based prediction of trajectories for socially compliant navigation. In Robotics: science and systems, volume 8, pages 193–200, 2012.
- Safe planning in dynamic environments using conformal prediction. IEEE Robotics and Automation Letters, 8(8):5116–5123, 2023a.
- Conformal prediction for stl runtime verification. In Proceedings of the ACM/IEEE 14th International Conference on Cyber-Physical Systems (with CPS-IoT Week 2023), pages 142–153, 2023b.
- Sample-efficient safety assurances using conformal prediction. In International Workshop on the Algorithmic Foundations of Robotics, pages 149–169. Springer, 2022.
- Multi-agent reachability calibration with conformal prediction. arXiv preprint arXiv:2304.00432, 2023.
- Stochastic mpc with multi-modal predictions for traffic intersections. In 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), pages 635–640. IEEE, 2022.
- Harris Papadopoulos. Inductive conformal prediction: Theory and application to neural networks. In Tools in artificial intelligence. Citeseer, 2008.
- Path planning using a dynamic vehicle model. In 2006 2nd International Conference on Information & Communication Technologies, volume 1, pages 781–786. IEEE, 2006.
- Recent advances in recurrent neural networks. arXiv preprint arXiv:1801.01078, 2017.
- A tutorial on conformal prediction. Journal of Machine Learning Research, 9(3), 2008.
- Conformal prediction under covariate shift. Advances in neural information processing systems, 32, 2019.
- Scalable safe long-horizon planning in dynamic environments leveraging conformal prediction and temporal correlations. ICRA, 2023.
- Unfreezing the robot: Navigation in dense, interacting crowds. In 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 797–803. IEEE, 2010.
- Reciprocal n-body collision avoidance. In Robotics Research: The 14th International Symposium ISRR, pages 3–19, 2011.
- Algorithmic learning in a random world, volume 29. Springer, 2005.
- Group-based motion prediction for navigation in crowded environments. In Conference on Robot Learning, pages 871–882. PMLR, 2022.
- Moving obstacle avoidance: A data-driven risk-aware approach. IEEE Control Systems Letters, 7:289–294, 2022.
- Interaction-aware probabilistic trajectory prediction of cut-in vehicles using gaussian process for proactive control of autonomous vehicles. IEEE Access, 9:63440–63455, 2021.
- Signal temporal logic control synthesis among uncontrollable dynamic agents with conformal prediction. arXiv preprint arXiv: 2312.04242, 2023.
- A gaussian process model for opponent prediction in autonomous racing. arXiv preprint arXiv:2204.12533, 2022.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.