Toward Intrinsic Force Sensing and Control in Parallel Soft Robots

With soft robotics being increasingly employed in settings demanding high and controlled contact forces, recent research has demonstrated the use of soft robots to estimate or intrinsically sense forces without requiring external sensing mechanisms. While this has mainly been shown in tendon-based continuum manipulators or deformable robots comprising of push-pull rod actuation, fluid drives still pose great challenges due to high actuation variability and nonlinear mechanical system responses. In this work, we investigate the capabilities of a hydraulic, parallel soft robot to intrinsically sense and subsequently control contact forces. A comprehensive algorithm is derived for static, quasi-static, and dynamic force sensing, which relies on fluid volume and pressure information of the system. The algorithm is validated for a single degree-of-freedom soft fluidic actuator. Results indicate that axial forces acting on a single actuator can be estimated with mean error of 0.56 ± 0.66 N within the validated range of 0-6 N in a quasi-static configuration. The force sensing methodology is applied to force control in a single actuator as well as the coupled parallel robot. It can be seen that forces are controllable for both systems, with the capability of controlling directional contact forces in case of the multidegree-of-freedom parallel soft robot.