Latest Papers

ASME Journal of Mechanisms and Robotics

  • Robust Multilegged Walking Robots for Interactions With Different Terrains
    on May 26, 2023 at 12:00 am

    AbstractThis paper explores the kinematic synthesis, design, and pilot experimental testing of a six-legged walking robotic platform able to traverse through different terrains. We aim to develop a structured approach to designing the limb morphology using a relaxed kinematic task with incorporated conditions on foot-environments interaction, specifically contact force direction and curvature constraints, related to maintaining contact. The design approach builds up incrementally starting with studying the basic human leg walking trajectory and then defining a “relaxed” kinematic task. The “relaxed” kinematic task consists only of two contact locations (toe-off and heel-strike) with higher-order motion task specifications compatible with foot-terrain(s) contact and curvature constraints in the vicinity of the two contacts. As the next step, an eight-bar leg image is created based on the “relaxed” kinematic task and incorporated within a six-legged walking robot. Pilot experimental tests explore if the proposed approach results in an adaptable behavior which allows the platform to incorporate different walking foot trajectories and gait styles coupled to each environment. The results suggest that the proposed “relaxed” higher-order motion task combined with the leg morphological properties and feet material allowed the platform to walk stably on the different terrains. Here we would like to note that one of the main advantages of the proposed method in comparison with other existing walking platforms is that the proposed robotic platform has carefully designed limb morphology with incorporated conditions on foot-environment interaction. Additionally, while most of the existing multilegged platforms incorporate one actuator per leg, or per joint, our goal is to explore the possibility of using a single actuator to drive all six legs of the platform. This is a critical step which opens the door for the development of future transformative technology that is largely independent of human control and able to learn about the environment through their own sensory systems.

Dexterity Analysis Based on Jacobian and Performance Optimization for Multi-Segment Continuum Robots

Abstract

This paper focuses on the performance analysis of multi-segment continuum robots, including reachable workspace and dexterity performance. Since excellent dexterity is an important feature of continuum robots, two local indices inspired by separating robotic Jacobian matrix, namely axiality and angularity dexterity, are introduced to explore the dexterity. Then, a Monte Carlo Method is adopted to simulate the distribution of local dexterity over the workspace. On this basis, the corresponding global indices in axiality and angularity are defined to assess global dexterity performance. To investigate the optimal kinematic performance, an objective function related to the segment lengths is designed under the consideration of reachable workspace and dexterity performance. Finally, Particle Swarm Optimization (PSO) algorithm is used to solve this optimization problem successfully. The optimal length distributions for two-segment and three-segment continuum robots are discovered. Most importantly, it is found that our method can also apply to general multi-segment continuum robots.
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