Trajectory Generation and Tracking based on Energy Minimization for a Four-Link Brachiation Robot

TL;DR

This paper presents a four-link brachiation robot model with an energy-efficient offline trajectory generator and a linear MPC for joint and Cartesian space tracking, demonstrating effective simulation results in trajectory tracking and obstacle avoidance.

Contribution

Introduces a novel brachiation robot model with an energy minimization-based trajectory generator and a dual-space MPC controller for improved motion control.

Findings

Robot achieves accurate trajectory tracking in simulation.

Energy minimization improves swing efficiency.

Robustness and obstacle avoidance demonstrated in simulations.

Abstract

Aiming to mimic the brachiation locomotion of primates, we establish a brachiation robot model capable of swinging between different bars. The robot's design is based on a four-link underactuated structure. We propose an offline trajectory generator with optimization for minimizing energy consumption, which is implemented by direct collocation method to generate joint-space trajectories. We also propose a linear Model Predictive Control (MPC) algorithm as the feedback controller. The proposed MPC concurrently tracks both trajectories in joint space and Cartesian space. In simulation experiments, we analyzed the influence of lower-to-upper arm length ratio and swing time on the motion performance. The simulation results also demonstrate the robot has satisfied ability in trajectory tracking, obstacle avoidance and robustness.