Carmen Visconte

Tendon-Driven Continuum Robots (TDCRs) are increasingly used in minimally invasive surgery and cluttered environments because of their compliance and dexterity. However, dense workspace characterization and configuration selection remain challenging because inverse kinematics must be solved in a highly redundant, nonlinear space under tendon-actuation constraints. Existing capability map frameworks do not directly address configuration-level tendon feasibility or dexterity-aware selection among feasible alternatives. This paper presents a database-driven CAP framework that combines piecewise constant curvature kinematics with particle swarm optimization to construct an offline library of configurations consistent with the prototype tendon-routing and command-mapping model over 180 workspace voxels and 54,000 voxel-orientation samples. For each feasible sample, pose residuals and Jacobian-based dexterity descriptors are computed offline and stored in the database. At runtime, the method retrieves feasible entries for a queried voxel and ranks them through a Pareto-based trade-off between combined pose residual and inverse manipulability. The output is a dexterity-aware representative configuration for the queried local neighbourhood, rather than a newly optimized exact-pose solution. Motion-capture validation on a custom two-segment TDCR shows millimetre-order position errors in the evaluated ROI.

Recent advances in mobile robotics have emphasized the need for systems capable of operating in unstructured environments, combining obstacle negotiation, stability, and adaptability. This study presents the preliminary design and testing of Brush.Q, an articulated ground robot featuring a novel structure distinct from existing wheel-legged robots, equipped with compliant brush-like wheels composed of multiple spokes. The main contribution is the experimental analysis of suspension capability across different wheel geometric profiles, combined with the assessment of obstacle-climbing performance. A simplified prototype was constructed to evaluate the effects of wheel rotation direction, spoke number, and spoke tapering. Results show that reducing the number of spokes improves obstacle-climbing at the expense of suspension, while higher spoke count and compliant geometry enhance suspension and stability. Spoke tapering improves obstacle climbing in the backward-facing configuration but consistently reduces suspension. Overall, these findings highlight the critical role of wheel geometry and the potential for reconfigurable spoked wheels to enhance adaptability and versatility in unstructured terrains.

Recent advances in mobile robotics have emphasized the need for systems capable of 2 operating in unstructured environments, combining obstacle negotiation, stability, and 3 adaptability. This study presents a preliminary design of an articulated ground robot, 4 Brush.Q, equipped with compliant brush-like wheels composed of multiple spokes. The 5 wheels occupy the majority of the robot’s track width, minimizing chassis exposure to 6 obstacles, and integrate passive compliance along with a flexible articulated structure to 7 enhance obstacle-climbing and suspension capabilities. To evaluate these capabilities, a 8 prototype was tested across various terrains and obstacle heights, assessing the effects 9 of wheel rotation direction, spoke number, and spoke tapering. Experimental results 10 demonstrate that reducing the number of spokes improves obstacle-climbing capability, 11 while a higher number of spokes and compliant geometry enhance suspension and stability. 12 Tapered spokes can increase obstacle negotiation but reduce suspension performance. 13 These findings highlight the critical role of wheel geometry in wheel-legged robots and 14 suggest the potential for reconfigurable spoked wheels that enhance a robot’s adaptability 15 and versatility in unstructured environments.