SearcharxivSearch

arXiv subjects

Fuchen Chen

Publications and source records attributed to Fuchen Chen.

3 recordsLinked to original sources

Vibration of Soft, Twisted Beams for Under-Actuated Quadrupedal Locomotion

Under-actuated compliant robotic systems offer a promising approach to mitigating actuation and control challenges by harnessing pre-designed, embodied dynamic behaviors. This paper presents Flix-Walker, a novel, untethered, centimeter-scale quadrupedal robot inspired by compliant under-actuated mechanisms. Flix-Walker employs flexible, helix-shaped beams as legs, which are actuated by vibrations from just two motors to achieve three distinct mobility modes. We analyze the actuation parameters required to generate various locomotion modes through both simulation and prototype experiments. The effects of system and environmental variations on locomotion performance are examined, and we propose a generic metric for selecting control parameters that produce robust and functional motions. Experiments validate the effectiveness and robustness of these actuation parameters within a closed-loop control framework, demonstrating reliable trajectory-tracking and self-navigation capabilities.

cs.RO

Tunable Dynamic Walking via Soft Twisted Beam Vibration

We propose a novel mechanism that propagates vibration through soft twisted beams, taking advantage of dynamically-coupled anisotropic stiffness to simplify the actuation of walking robots. Using dynamic simulation and experimental approaches, we show that the coupled stiffness of twisted beams with terrain contact can be controlled to generate a variety of complex trajectories by changing the frequency of the input signal. This work reveals how ground contact influences the system's dynamic behavior, supporting the design of walking robots inspired by this phenomenon. We also show that the proposed twisted beam produces a tunable walking gait from a single vibrational input.

cs.RO

A dimension reduction method with applications for coefficient inversion of diffusion equations

In this paper, we present a dimension reduction method to reduce the dimension of parameter space and state space and efficiently solve inverse problems. To this end, proper orthogonal decomposition (POD) and radial basis function (RBF) are combined to represent the solution of forward model with a form of variable separation. This POD-RBF method can be used to efficiently evaluate the model's output. A gradient regularization method is presented to solve the inverse problem with fast convergence. A generalized cross validation method is suggested to select the regularization parameter and differential step size for the gradient computation. Because the regularization method needs many model's evaluations. This is desirable for POD-RBF method. Thus, the POD-RBF method is integrated with the gradient regularization method to provide an efficient approach to solve inverse problems. We focus on the coefficient inversion of diffusion equations using the proposed approach. Based on different types of measurement data and different basis functions for coefficients, we present a few numerical examples for the coefficient inversion. The numerical results show that accurate reconstruction for the coefficient can be achieved efficiently.

math.NA