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.

Markov Chain Monte Carlo Parameter Estimation for Nonzero Slip Models of Wheeled Mobile Robots: A Skid-Steer Case Study

Abstract

An accurate modeling, simulation, and estimation of the wheel-terrain interaction and its effects on a robot movement plays a key role in control and navigation tasks, specially in constantly changing environments. We study the calibration of wheel slip models using Particle Markov Chain Monte Carlo methods to approximate the posterior distributions of their parameters. In contrast to classic identification approaches, considering the parameters as random variables allows to obtain a probability measure of the parameter estimations and subsequently propagate their uncertainty to wheel slip-related variables. Extensive simulation and experimental results showed that the proposed methodology can effectively get reliable posterior approximations from noisy sensor measurements in changing terrains. Validation tests also include the applicability assessment of the proposed methodology by comparing it with the integrated prediction error minimization methodology. Field results presented up to 66% of improvement in the robot motion prediction with the proposed calibration approach.
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