Research on Integrated Control Strategies for Autonomous Robot Navigation: Trajectory Tracking and Intelligent Path Planning in Dynamic Environments

With the rapid development of intelligent manufacturing and automation technologies, automated robots have become crucial in both industrial and service sectors. Trajectory tracking technology ensures that robots follow predefined paths accurately, while path planning is responsible for determining the optimal route for robots to navigate through complex environments. The integration of these two technologies is particularly important in dynamic settings, as it directly impacts the stability and operational efficiency of robots. Current research focuses on enhancing the autonomy and flexibility of robots in uncertain environments through advanced algorithms such as model predictive control and sampling-based path planning. This paper provides a comprehensive review of the state-of-the-art in automated robot trajectory tracking and path planning technologies, discusses the challenges faced in practical applications, and explores future research directions. The role of visual perception in improving the efficiency of path planning is also highlighted, with particular attention to the impact of real-time object detection technologies on autonomous navigation.

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Publication Details

Journal
European Journal of AI Computing & Informatics
Published
2025-04-21
DOI
https://doi.org/10.71222/a5kbyb85
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.00
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article

Research on Integrated Control Strategies for Autonomous Robot Navigation: Trajectory Tracking and Intelligent Path Planning in Dynamic Environments

Dajun Tao
European Journal of AI Computing & Informatics
Robotic Path Planning Algorithms
article

Research on Integrated Control Strategies for Autonomous Robot Navigation: Trajectory Tracking and Intelligent Path Planning in Dynamic Environments

Dajun Tao
article en

Abstract

With the rapid development of intelligent manufacturing and automation technologies, automated robots have become crucial in both industrial and service sectors. Trajectory tracking technology ensures that robots follow predefined paths accurately, while path planning is responsible for determining the optimal route for robots to navigate through complex environments. The integration of these two technologies is particularly important in dynamic settings, as it directly impacts the stability and operational efficiency of robots. Current research focuses on enhancing the autonomy and flexibility of robots in uncertain environments through advanced algorithms such as model predictive control and sampling-based path planning. This paper provides a comprehensive review of the state-of-the-art in automated robot trajectory tracking and path planning technologies, discusses the challenges faced in practical applications, and explores future research directions. The role of visual perception in improving the efficiency of path planning is also highlighted, with particular attention to the impact of real-time object detection technologies on autonomous navigation.

European Journal of AI Computing & InformaticsVol. 1(1)
Flex (United States) (US)
Openalex Percentile: Top 86%
Robotic Path Planning Algorithms
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