Latest Papers

ASME Journal of Mechanisms and Robotics

  • Design of Reconfigurable Articulated Walking Mechanisms for Diverse Motion Behaviors
    on March 20, 2025 at 12:00 am

    AbstractLegged robots are able to move across irregular terrains and those based on 1-degree-of-freedom planar linkages can be energy efficient but are often constrained by a limited range of gaits which can limit their locomotion capabilities considerably. This article reports the design of novel reconfigurable parallel linkages that not only produce different walking patterns but also realize behaviors beyond locomotion. Experiments with an implemented wearable device able to guide the lower extremity through multiple human-like walking trajectories are presented and the preliminary results validate the proposed approach.

  • Modeling, Kinematics, and Dynamics of a Rigid-Flexible Coupling Spring-Cable-Driven Parallel Robot
    on March 20, 2025 at 12:00 am

    AbstractConventional parallel robots are made of rigid materials for the purpose of fast and accurate localization, exhibiting limited performance in large-scale operations. Inspired by the softness and natural compliance of biological systems, this article proposes a rigid-flexible coupling cable-driven parallel robot. The concept of flexible cable and spring hybrid and working principle are introduced. The kinematics of single module and multiple modules connected in series are analyzed and equations are given, and the Lagrange equation is used to establish dynamic models. Finally, two methods are used to validate the kinematics and dynamics. One is to draw the specific structure with the posture of the end-effector and measure the cable length to compare it with the analytical solution in the kinematic model. The other is to build the structure and joint characteristics in simulink, given the posture of the end-effector and the external force/torque, the cable length and the force applied are compared with those obtained from the dynamic model. The reasonableness of the mechanism and the feasibility of the kinematic and dynamic models are verified.

Targeted Sampling Dynamic Window Approach: A Path-Aware Dynamic Window Approach Sampling Strategy for Omni-Directional Robots

Abstract

This paper describes a sampling strategy for the dynamic window approach (DWA), a local path planner, for omni-directional robot motion planning. An efficient local planner allows the robot to quickly respond to dynamic obstacles and ensures that commanded velocities meet the dynamic constraints of the robot. While typical DWA implementations sample the velocity space evenly, we propose that targeted sampling (TS) will result in a more fine-grained search of the relevant velocity space, leading to better control and performance in space-constrained environments. Our TS-DWA strategy is informed by the global planned path, allowing us to sample more velocities in the general path direction. We employ a polar velocity generator to selectively sample velocities and couple angular velocity samples to the path curvature. A bias for angular velocity is added for robots with a preferred heading, such as robots with forward-mounted sensors, to quickly turn toward the desired direction for better sensing. The strategy is implemented as a robot operating system (ROS) navigation stack local_planner plugin and tested in simulation with Gazebo using an omni-directional robot platform. Experiments show that as the space around the simulated robot gets smaller, our proposed sampling strategy results in more successful navigation trials to the goal in space-constrained environments compared to other commonly used methods like DWA and timed-elastic-band, where planning fails or oscillates. TS-DWA was also deployed on the Vision60 quadrupedal robot to demonstrate navigation through narrow corridors in the real world.

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