Automated Robot Trajectory Tracking and Path Planning Technology Research

Dajun Tao

doi:10.62051/ijcsit.v4n1.39

Authors

Dajun Tao

DOI:

https://doi.org/10.62051/ijcsit.v4n1.39

Keywords:

Automated robots, Trajectory tracking, Path planning

Abstract

The widespread application of automation robots in both industrial and service sectors has generated a significant demand for efficient and precise trajectory tracking and path planning technologies. Trajectory tracking technology aims to ensure that robots move accurately along predetermined paths, while path planning is responsible for devising the optimal route for robots to navigate through complex environments with multiple constraints. The integration of these two aspects is especially crucial in dynamic settings, directly impacting the stability and operational efficiency of robots. Current research focuses on enhancing the autonomy and flexibility of robots in complex and uncertain environments through advanced algorithms such as model predictive control and sampling-based path planning. This paper will systematically explore the current state and development trends of automation robot trajectory tracking and path planning technologies, analyze the challenges encountered in practical applications, and anticipate future directions.

Downloads

Download data is not yet available.

References

[1] Gao M, Yan T, Fu W, et al. Automated flight technology for integral path planning and trajectory tracking of the UAV [J]. Drones, 2023, 8(1): 9.

[2] BaniHani S, Hayajneh M R M, Al-Jarrah A, et al. New control approaches for trajectory tracking and motion planning of unmanned tracked robot [J]. Advances in Electrical and Electronic Engineering, 2021, 19(1): 42-56.

[3] Gasparetto A, Boscariol P, Lanzutti A, et al. Path planning and trajectory planning algorithms: A general overview [J]. Motion and operation planning of robotic systems: Background and practical approaches, 2015: 3-27.

[4] Martınez-Alfaro H, Gomez-Garcıa S. Mobile robot path planning and tracking using simulated annealing and fuzzy logic control [J]. Expert Systems with Applications, 1998, 15(3-4): 421-429.

[5] Li I H, Chien Y H, Wang W Y, et al. Hybrid intelligent algorithm for indoor path planning and trajectory-tracking control of wheeled mobile robot [J]. International Journal of Fuzzy Systems, 2016, 18: 595-608.