Latest Papers

ASME Journal of Mechanisms and Robotics

  • Integrated Wheel–Foot–Arm Design of a Mobile Platform With Linkage Mechanisms
    on March 20, 2024 at 12:00 am

    AbstractInspired by lizards, a novel mobile platform with revolving linkage legs is proposed. The platform consists of four six-bar bipedal modules, and it is designed for heavy transportation on unstructured terrain. The platform possesses smooth-wheeled locomotion and obstacle-adaptive legged locomotion to enhance maneuverability. The kinematics of the six-bar bipedal modules is analyzed using the vector loop method, subsequently ascertaining the drive scheme. The foot trajectory compensation curve is generated using the fixed-axis rotation contour algorithm, which effectively reduces the centroid fluctuation and enables seamless switching between wheels and legs. When encountering obstacles, the revolving linkage legs act as climbing arms, facilitating seamless integration of wheel, foot, and arm. A physical prototype is developed to test the platform on three typical terrains: flat terrain, slope, and vertical obstacle. The experimental results demonstrated the feasibility of the platform structure. The platform can climb obstacles higher than its own height without adding extra actuation.

Multiparameter Real-World System Identification Using Iterative Residual Tuning

Abstract

In this work, we consider the problem of nonlinear system identification using data to learn multiple and often coupled parameters that allow a simulator to more accurately model a physical system or mechanism and close the so-called reality gap for more accurate robot control. Our approach uses iterative residual tuning (IRT), a recently developed derivative-free system identification technique that utilizes neural networks and visual observation to estimate parameter differences between a proposed model and a target model. We develop several modifications to the basic IRT approach and apply it to the system identification of a five-parameter model of a marble rolling in a robot-controlled labyrinth game mechanism. We validate our technique both in simulation—where we outperform two baselines—and on a real system, where we achieve marble tracking error of 4% after just five optimization iterations.
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