Safety-Critical Whole-Body Control for Humanoid Robots via Input-to-State Safe Control Barrier Functions
2026-05-25 • Robotics
Robotics
AI summaryⓘ
The authors developed a control system for humanoid robots that helps keep them safe while moving and interacting in complex human environments. Their system uses multiple layers: one plans the robot’s motions, another adjusts these plans to avoid safety issues even if there are unexpected problems, and the last makes sure the robot moves correctly and stably. They tested their method in simulations and with real robots, showing it keeps the robot safer despite uncertainties and disturbances. This approach ensures the robot respects physical limits and avoids collisions while performing tasks like walking or balancing.
Humanoid robotsSafety-critical controlKinematic constraintsControl barrier functionsInput-to-state safetyWhole-body controlTrajectory trackingModel uncertaintiesDynamic feasibilityContact stability
Authors
Kwanwoo Lee, Sanghyuk Park, Gyeongjae Park, Myeong-Ju Kim, Jaeheung Park
Abstract
Safety-critical control is essential for humanoid robots operating in complex human-centered environments, where physical safety constraints such as joint limits, self-collision avoidance, obstacle avoidance, and workspace boundaries must be satisfied during real-robot operation. However, existing approaches remain limited because kinematic safety guarantees can be degraded in the presence of unknown disturbances, such as model uncertainties, trajectory-tracking errors, and external perturbations. This paper presents a hierarchical safety-critical whole-body control framework for humanoid robots based on input-to-state safe control barrier functions (ISSf-CBFs). The proposed architecture integrates a kinematic-level whole-body controller (KinWBC), an ISSf-CBF safety filter, and a dynamic-level whole-body controller (DynWBC). KinWBC generates nominal joint-motion references from prioritized tasks; the ISSf-CBF filter minimally modifies these references to satisfy kinematic safety constraints under bounded disturbances; and DynWBC tracks the filtered references while enforcing full-body dynamic feasibility and contact stability. Safety constraints are imposed on a whole-body kinematic model, and the ISSf-CBF parameters are conservatively tuned so that the resulting kinematic safety guarantees can be transferred to full-order humanoid dynamics under unknown disturbances. Simulation and real-robot experiments demonstrate that the proposed framework improves safety margins under model mismatch and reliably enforces multiple safety constraints in real time during locomotion, teleoperation, and single-leg balancing with hand control. Project website: https://kwlee365.github.io/SafeWBC-Website/