Abstract

Generating collision-free motions in dynamic environments is a challenging problem for high-dimensional robotics, particularly under real-time constraints. Control Barrier Functions (CBFs), widely utilized in safety-critical control, have shown significant potential for motion generation. However, for high-dimensional robot manipulators, existing QP formulations and CBF-based methods rely on positional information, overlooking higher-order derivatives such as velocities. This limitation may lead to reduced success rates, decreased performance, and inadequate safety constraints. To address this, we construct time-varying CBFs (TVCBFs) that consider dynamic obstacles. Our approach leverages recent developments on distance fields for articulated manipulators, a differentiable representation that enables the mapping of objects' position and velocity into the robot's joint space, offering a comprehensive understanding of the system's interactions. This allows the manipulator to be treated as a point-mass system thus simplifying motion generation tasks. Additionally, we introduce a time-varying control Lyapunov function (TVCLF) to enable whole-body contact motions. Our approach integrates the TVCBFs, TVCLF, and manipulator physical constraints within a unified QP framework. We validate our method through simulations and comparisons with state-of-the-art approaches, demonstrating its effectiveness on a 7-axis Franka arm in real-world experiments. Source codes, experimental data and videos are available on the project webpage: https://sites.google.com/view/sdfcdf-tvcbfs-qp.

Bibtex reference

@inproceedings{Chi26ICRA,
	author={Chi, X. and Huang, J. and Li, Y. and Dai, B. and Liu, Z. and Calinon, S.},
	title={Dynamic Safety-Critical Motion Generation in Configuration Space Using Differentiable Distance Fields for Manipulators},
	booktitle={Proc.\ {IEEE} Intl Conf.\ on Robotics and Automation ({ICRA})},
	year={2026},
	pages={}
}

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