cs.ROSep 22, 2026

Real-Time Whole-Body Safe Motion Generation for Multi-Segment Tendon-Driven Continuum Robots

Authors: Fangju Yang, Siyi Ma, Tonghao Guan, Tingcong Liu, Hang Yang, Zhengqiang Zhang, Jian S. Dai, Ke Wu

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Abstract

Real-time motion generation for tendon-driven continuum robots requires accurate modeling of nonuniform bending and whole-body collision avoidance. This paper presents a unified actuation-space framework for planar multi-segment tendon-driven continuum robots. An energy-based variable-curvature model captures spatially varying tendon spacing and bending stiffness and provides analytical Jacobians for differential inverse kinematics and safety monitoring. A multipoint CBF-QP enforces backbone clearance under obstacle motion and actuation-velocity bounds, while its decision dimension depends only on the number of independently actuated segments. The model closely agrees with GVS references, with a maximum curvature error of 5.223×10−2 m−15.223 \times 10^{-2}\,\mathrm{m}^{-1}. Over 100 MuJoCo trials, the proposed method achieves collision-free success rates of 96% and 100% in static and dynamic scenarios, respectively, compared with approximately 60% and 80% without CBF constraints. Hole-traversal tests further demonstrate safe motion in constrained environments. With 600 backbone monitoring points, the mean control-step time is 6.66 ms, demonstrating real-time whole-body safe motion generation.

Figures & tables

Fig. 1: Real-time whole-body safe motion generation for continuum robots. (A) Robot and kinematics. (B) Whole-body collision avoidance. (C) Real-time CBF-QP control framework.
ParameterSymbolValue or profileUnit
Number of segmentsNN33–
Total backbone lengthLL0.300.30m
Segment lengthsLiL_{i}[0.12, 0.10, 0.08][0.12,\,0.10,\,0.08]m
Young’s moduliEiE_{i}[6.0, 7.0, 5.5][6.0,\,7.0,\,5.5]MPa
Diameter profileD(s)D(s)6.4×10−3(1−0.5s/L)6.4\times 10^{-3}(1-0.5s/L)m
Second moment of areaI(s)I(s)πD4(s)/64\pi D^{4}(s)/64m4\mathrm{m^{4}}
TABLE I: Simulation Parameters
Fig. 2: Kinematic validation against GVS: shape comparison and segment-wise curvature errors.
Fig. 3: Sim-to-sim validation of real-time whole-body safe motion generation in MuJoCo: static and dynamic obstacle avoidance and hole traversal.
CBF sampling pointsΔs [m]\boldsymbol{\Delta s}\,[\mathrm{m}]Mean control-step time (ms)
1000.007581.1692
2000.003771.9870
3000.002512.9671
4000.001883.6831
5000.001505.0753
6000.001256.6641
TABLE II: CBF Sampling Density and Computational Cost

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