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- Title
Driving Path Tracking Strategy of Humanoid Robot Based on Improved Pure Tracking Algorithm.
- Authors
Yuan Wei; Haoran Li; Zhigang Zhou; Dongdong Chen
- Abstract
To improve the path-tracking accuracy of humanoid robot driving, this paper proposes a path-tracking strategy for humanoid robot vehicle going based on an improved pure tracking algorithm. The strategy takes into account the influence of vehicle speed and path curvature on the foresight distance. The vehicle's speed is adjusted according to the path curvature changes, enabling dynamic adjustments of the foresight distance and steering wheel turning angle. A controller is designed using a fuzzy control algorithm to minimise the path-tracking error. The vehicle's lateral and heading errors are taken as the fuzzy controller inputs, while the steering wheel angle compensation is taken as the output. The sum of the feedforward and compensation of the steering wheel angle is used as the control amount of the vehicle's steering wheel angle. To reduce the computational amount and save calculation time, the movement primitives of robot driving motion are extracted and connected to design the robot driving motion module. This module takes the vehicle parameters as input for the motion model and outputs the corresponding robot-related joint angles. The humanoid robot NAO and a miniature electric vehicle are the test platforms. In the Linux system, the robot's NAOqi system and the vehicle's main controller communicate through the same local area network, enabling the robot NAO to drive the vehicle in real-time. Experimental results demonstrate that the proposed strategy significantly improves the path-tracking accuracy of humanoid robot vehicle driving compared to traditional algorithms.
- Subjects
HUMANOID robots; TRACKING algorithms; ELECTRIC vehicles testing; LOCAL area networks; ROBOT motion
- Publication
IAENG International Journal of Applied Mathematics, 2024, Vol 54, Issue 2, p286
- ISSN
1992-9978
- Publication type
Article