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.
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Dajun Tao (2024) studied this question.
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