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Error-State Model Predictive Path Integral Control of Tendon-Driven Continuum Robots using Cosserat Rod Dynamics with
E Arefinia1, N Feizi2, F C Pedrosa1
1Department of Electrical and Computer Engineering, Western University, London, ON, Canada, and Canadian Surgical Technologies and Advanced Robotics (CSTAR), University Hospital, LHSC, London, ON, Canada.
IEEE Robotics and Automation Letters
|April 3, 2026
Summary
This study introduces an error-state Model Predictive Path Integral (MPPI) controller for tendon-driven continuum robots (TDCRs), enhancing path accuracy and computational efficiency. The novel framework outperforms existing methods in robotic control applications.
Area of Science:
- Robotics
- Control Systems Engineering
- Computational Mechanics
Background:
- Continuum robots require precise control for complex tasks.
- Existing control methods for tendon-driven continuum robots (TDCRs) face challenges in accuracy and computational efficiency.
Purpose of the Study:
- To develop an advanced Model Predictive Path Integral (MPPI) framework for TDCRs.
- To improve tracking accuracy and computational performance in robotic control.
Main Methods:
- Formulated tracking-error dynamics on a Lie group for precise pose geometry.
- Developed a nonlinear Cosserat-rod model for TDCR dynamics, updated rapidly.
- Implemented an uncertainty-aware MPPI controller with adaptive cost and exponential weighting.
Main Results:
- The proposed MPPI framework achieved superior accuracy compared to conventional MPC, Lie-group MPC, and offline IQL.
- Demonstrated significantly better computational efficiency than MPC.
- The model is adaptable to multi-segment TDCRs and can account for tendon friction.
Conclusions:
- The error-state MPPI framework offers a highly accurate and computationally efficient solution for TDCR control.
- This approach advances the capabilities of continuum robots in precision-demanding applications.
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