Recently, a new concept for continuum robots capable of producing macro-scale and micro-scale motion has been presented. These robots achieve their multi-scale motion capabilities by coupling direct actuation of push-pull backbones for macro-motion with indirect actuation whereby the equilibrium pose is altered to achieve micro-scale motion. This paper presents a first attempt at explaining the micro-motion capabilities of these robots from a modeling perspective. This paper presents the macro- and micro-motion kinematics of a single-segment continuum robot by using statics coupling effects among its subsegments. Experimental observations of the micro-scale motion demonstrate a turning point behavior which could not be explained well using the current modeling methods. We present a simplistic modeling approach that introduces two calibration parameters to calibrate the moment coupling effects among the subsegments of the robot. It is shown that these two parameters can reproduce the turning point behavior at the micro-scale. The instantaneous macro- and micro-scale kinematics Jacobians and the calibration parameters identification Jacobian are derived. The modeling approach is verified against experimental data showing that our simplistic modeling approach can capture the experimental motion data with the RMS position error of 5.82 μm if one wishes to fit the entire motion profile with the turning point. If one chooses to exclude motions past the turning point, our model can fit the experimental data with an accuracy of 4.76 μm.
Simplified Kinematics of Continuum Robot Equilibrium Modulation via Moment Coupling Effects and Model Calibration
Manuscript received August 6, 2018; final manuscript received June 20, 2019; published online July 18, 2019. Assoc. Editor: Shaoping Bai.
- Views Icon Views
- Share Icon Share
- Search Site
Wang, L., Del Giudice, G., and Simaan, N. (July 18, 2019). "Simplified Kinematics of Continuum Robot Equilibrium Modulation via Moment Coupling Effects and Model Calibration." ASME. J. Mechanisms Robotics. October 2019; 11(5): 051013. https://doi.org/10.1115/1.4044162
Download citation file: