Abstract

The jumping robot has been a hot research field due to its prominent obstacle-climbing ability and excellent capacity in terrain adaptation and autonomous movement. However, huge impact between the robot and the ground when landing may cause structure damage, unbalanced movement, and even system crash. Therefore, trajectory planning of the jumping process has been a great challenge in robotic research, especially for the robot with varying underactuated and redundant joints. An intermittent jumping quadruped robot driven by pneumatic muscle actuators (PMAs) and owning variable redundant and underactuated joints designed in a previous study is taken as the study object. This paper divides the problem of trajectory planning into trajectory planning in the centroid space and joint space. Trajectory planning of different jumping phases in the centroid space adopts the scheme of minimizing the peak reaction force from the ground, then trajectory planning of the joint space is performed obeying the principle of minimizing consumed active torques. A jumping experiment is performed and validates the effectiveness of the proposed trajectory algorithm.

Highlights

  • Legged robots have been a hot research field due to excellent mobility on rugged terrain [1,2,3]

  • Trajectory planning of different jumping phases in the task space adopts the scheme of minimizing the peak reaction force from the ground, trajectory planning of the joint space would be performed obeying the principle of minimizing consumed active torques

  • This paper studies trajectory planning of an intermittent jumping quadruped robot driven by pneumatic muscle actuators and owning variable redundant and underactuated joints

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Summary

Introduction

Legged robots have been a hot research field due to excellent mobility on rugged terrain [1,2,3] These robots have various motion modes, such as running, hopping, walking, and jogging [4,5,6]. Wan et al proposed an optimized jumping motion of a four-leg robot and analyzed numerical optimization results for different takeoff postures [11]. Heerden and Kawamura adopted the A-star path planning algorithm to realize jumping trajectory generation considering reducing backwards and compliant landing [13].

Dynamic Modeling of the Intermittent Jumping Quadruped Robot
Trajectory Planning of the Intermittent Jumping Quadruped Robot
Experiments and Discussions
Conclusion
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