Prioritized Multi-task Motion Coordination of Physically Constrained Quadruped Manipulators

TL;DR

This paper introduces a new motion coordination framework for quadruped robots with manipulators to handle complex tasks efficiently.

Contribution

A novel motion coordination framework using multi-task prioritization and null-space projection for quadruped manipulators.

Findings

The framework adapts to three prioritized tasks including trajectory tracking and constraint satisfaction.

Experiments show the robot achieves end-effector tracking with less than 3 cm error.

The method is validated through both simulation and physical robot testing.

Abstract

Quadruped manipulators can use legs to mimic legged animals for crossing unstructured environments. They can also use a bionic arm to execute manipulation tasks. The increasing demands for such robots have pushed research progress. However, there remain challenging works in their usage of a high degree of freedom. To solve this redundant problem, we propose a novel motion coordination framework based on multi-task prioritization and null-space projection. The framework can adaptively generate optimal motion for different parts of the robot considering 3 prioritized tasks. The tasks include end-effector trajectory tracking, motion redistribution to meet physical constraints, and manipulability enhancement. The motion is then executed by a whole-body controller incorporating dynamics, inverse kinematics, multiobjective priorities, and force constraints. Experiments both in simulation and on the robot platform validate the advantages and effectiveness of the algorithm. The robot can finish robust and accurate operational space end-effector tracking with errors less than 3 cm.

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