KINEMATIC OPTIMISATION OF SOFT ROBOTIC MANIPULATORS FOR MEDICAL INTERVENTION

Abstract

Soft robotic manipulators are increasingly investigated for minimally invasive medical intervention because their intrinsic compliance allows safe interaction with delicate anatomical structures while their continuum architecture enables navigation through tortuous natural or surgically created pathways. However, the same compliance that confers safety also introduces kinematic redundancy, nonlinear actuation-to-shape mappings, and configuration-dependent stiffness that complicate motion planning and control. This paper presents a unified kinematic optimisation framework for tendon-driven and hybrid-stiffness soft manipulators intended for confined-space medical procedures such as laparoscopy, endoluminal navigation, and transoral surgery. Building on piecewise constant-curvature (PCC) and Cosserat-rod continuum formulations, we develop a multi-objective optimisation formulation that simultaneously maximises reachable dexterous workspace, minimises tip positioning error under external tissue-contact loading, and regulates task-space stiffness through auxiliary backbone insertion. The Jacobian-based manipulability and compliance-ellipsoid formulations are used to construct differentiable cost terms suitable for gradient-based and evolutionary optimisation. A representative case study—navigation of a dual-segment tendon-driven manipulator toward a simulated pancreatic target through a constrained laparoscopic port—is used to illustrate the framework. Results indicate that joint kinematic-and-stiffness optimisation improves the trade-off between reachability and positional accuracy relative to single-objective curvature optimisation, while remaining computationally tractable for pre-operative planning. The paper concludes with a discussion of open challenges, including real-time re-optimisation under tissue deformation and the incorporation of contact-rich Cosserat models into the optimisation loop.