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Safe Probabilistic Planning for Human-Robot Interaction using Conformal Risk Control

arXiv 2603.10392 ↗First posted 11 Mar 2026cs.RO cs.AIcited by 0

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Abstract (arXiv)

In this paper, we present a novel probabilistic safe control framework for human-robot interaction that combines control barrier functions (CBFs) with conformal risk control to provide formal safety guarantees while considering complex human behavior. The approach uses conformal risk control to quantify and control the prediction errors in CBF safety values and establishes formal guarantees on the probability of constraint satisfaction during interaction. We introduce an algorithm that dynamically adjusts the safety margins produced by conformal risk control based on the current interaction context. Through experiments on human-robot navigation scenarios, we demonstrate that our approach significantly reduces collision rates and safety violations as compared to baseline methods while maintaining high success rates in goal-reaching tasks and efficient control. The code, simulations, and other supplementary material can be found on the project website: https://jakeagonzales.github.io/crc-cbf-website/.

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References · 21

  1. 2019Control Barrier Functions: Theory and Applicationscited by 332
  2. 2022Conformal Risk Controlcited by 290
  3. 2022Conformal Inference for Online Prediction with Arbitrary Distribution Shiftscited by 123
  4. 2015Model Predictive Path Integral Control using Covariance Variable Importance Samplingcited by 122
  5. 2022Safe Planning in Dynamic Environments using Conformal Predictioncited by 112
  6. 2020Learning Control Barrier Functions from Expert Demonstrationscited by 88
  7. 2017Multimodal Probabilistic Model-Based Planning for Human-Robot Interactioncited by 50
  8. 2022Adaptive Conformal Prediction for Motion Planning among Dynamic Agentscited by 46
  9. 2023Conformal Decision Theory: Safe Autonomous Decisions from Imperfect Predictionscited by 46
  10. 2023How to Train Your Neural Control Barrier Function: Learning Safety Filters for Complex Input-Constrained Systemscited by 40
  11. 2020Guaranteeing Safety of Learned Perception Modules via Measurement-Robust Control Barrier Functionscited by 32
  12. 2024CoBL-Diffusion: Diffusion-Based Conditional Robot Planning in Dynamic Environments Using Control Barrier and Lyapunov Functionscited by 30
9 more
  1. 2016Robustness of Control Barrier Functions for Safety Critical Controlcited by 29
  2. 2023Non-Exchangeable Conformal Risk Controlcited by 29
  3. 2020Learning Hybrid Control Barrier Functions from Datacited by 24
  4. 2020Learning Barrier Functions for Constrained Motion Planning with Dynamical Systemscited by 17
  5. 2024Robust Control Barrier Functions using Uncertainty Estimation with Application to Mobile Robotscited by 6
  6. 2023Robust Safety under Stochastic Uncertainty with Discrete-Time Control Barrier Functionscited by 5
  7. 2024Safety-Critical Control with Uncertainty Quantification using Adaptive Conformal Predictioncited by 5
  8. 2024Safe Decentralized Multi-Agent Control using Black-Box Predictors, Conformal Decision Policies, and Control Barrier Functionscited by 4
  9. 2023Robust Control Barrier Functions with Uncertainty Estimationcited by 3

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