JOURNAL ARTICLE

A Motion Planning Approach for Nonprehensile Manipulation and Locomotion Tasks of a Legged Robot

Guoteng ZhangShugen MaYayi ShenYibin Li

Year: 2020 Journal:   IEEE Transactions on Robotics Vol: 36 (3)Pages: 855-874   Publisher: Institute of Electrical and Electronics Engineers

Abstract

Nonprehensile manipulation produces underconstraint motions that are sensitive to environmental dynamics. Legged locomotion constitutes a floating-based movement, whose dynamic is underactuated with respect to the inertial frame. When these two tasks are combined, system motion planning and control are complex due to their inherent underactuated features. This article presents a motion planning framework for a legged robot that uses its limbs for nonprehensile manipulation, as well as locomoting motions. First, issues related to the description of the robot-object-environment system and the task are presented. The velocity constraint that prevents separation and the force constraint that restricts interactive forces are then integrated into the system dynamic model to produce bounds on the system acceleration as a function of the system state. Then, we solve the motion planning problem by reducing the system dimensions in operational space and programming feasible trajectories within the phase plane. This approach is employed to control the quadruped robot TITAN-VIII to manipulate objects and locomote itself using Drive Mode, Inchworm Mode, Scoot Mode, and Throw Mode. Experimental results obtained through simulations and physical tests are reported to demonstrate the effectiveness of our approach.

Keywords:
Underactuation Robot Control theory (sociology) Motion planning Computer science Control engineering Acceleration Inertial frame of reference Motion control Simulation Engineering Artificial intelligence Control (management) Physics

Metrics

26
Cited By
1.88
FWCI (Field Weighted Citation Impact)
38
Refs
0.83
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Robotic Locomotion and Control
Physical Sciences →  Engineering →  Biomedical Engineering
Robot Manipulation and Learning
Physical Sciences →  Engineering →  Control and Systems Engineering
Prosthetics and Rehabilitation Robotics
Physical Sciences →  Engineering →  Biomedical Engineering
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