title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ð° Ð¿Ð»Ð°Ð½Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÑÑÐ°ÐµÐºÑÐ¾ÑÐ¸Ð¸ Ð´Ð²Ð¸Ð¶ÐµÐ½Ð¸Ñ Ð¼Ð¾Ð±Ð¸Ð»ÑÐ½Ð¾Ð³Ð¾ ÑÐ¾Ð±Ð¾ÑÐ°
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Development of an algorithm for planning the trajectory of a mobile robot
Creators: name: Ð¯Ð½ ÐÑÐ¹Ð´Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: Ð¼Ð¾Ð±Ð¸Ð»ÑÐ½ÑÐ¹ ÑÐ¾Ð±Ð¾Ñ
Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½Ð¾Ð³Ð¾ Ð¿Ð¾ÑÐµÐ½ÑÐ¸Ð°Ð»ÑÐ½Ð¾Ð³Ð¾ Ð¿Ð¾Ð»Ñ apf
Ð¼ÐµÑÐ¾Ð´ Ð´Ð¸Ð½Ð°Ð¼Ð¸ÑÐµÑÐºÐ¾Ð³Ð¾ Ð¾ÐºÐ½Ð° dwa
Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼ a*
Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼ rrt
Ð³Ð»Ð¾Ð±Ð°Ð»ÑÐ½Ð¾Ðµ Ð¿Ð»Ð°Ð½Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð¿ÑÑÐ¸
Ð´Ð¸Ð½Ð°Ð¼Ð¸ÑÐµÑÐºÐ¾Ðµ Ð¸Ð·Ð±ÐµÐ³Ð°Ð½Ð¸Ðµ Ð¿ÑÐµÐ¿ÑÑÑÑÐ²Ð¸Ð¹
n-Ð¹ Ð¿Ð¾ÑÑÐ´Ð¾Ðº ÐºÑÐ¸Ð²ÑÑ Ð±ÐµÐ·ÑÐµ
mobile robot
artificial potential field algorithm apf
dynamic window method dwa
a* algorithm
rrt algorithm
global path planning
dynamic obstacle avoidance
n-th order bezier curves

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description: With the rapid development of the new generation of artificial intelligence and Internet of Things technologies, mobile robotics has become widespread. Among them, the autonomous trajectory planning technology of mobile robots is a key technology to realize their autonomous driving and obstacle avoidance, and is also one of the main widely used technologies. It is The study is devoted to mobile robots and their capabilities in real time and dynamic obstacle avoidance when planning a route. First, we propose a grid map obstacle preprocessing method that covers the interior space of concave obstacles to ensure route feasibility, while effectively reducing the number of grid nodes searched by the A* algorithm and improving the efficiency of path search. Secondly, to realize static global route planning, we compared the widely used global route planning algorithms, selected the A* algorithm, and optimized it to solve existing problems. By improving the heuristic function and weighting factor, the number of node traversals is reduced and the search efficiency is improved. B At the same time, the Bezier curve method is used to smooth the trajectory and reduce the rotation angle. Then, for dynamic local route planning, we studied the APF algorithm and the DWA algorithm in detail. By comparing the advantages and disadvantages of the algorithm and taking into account factors such as algorithm fusion, we selected the lightweight APF algorithm and optimized its repulsion field to solve the problem of unreachable target points and local interference. minimums. Finally, considering the problem of hybrid trajectory planning in a dynamic and complex environment, we propose a hybrid trajectory planning method based on combining the improved A* algorithm and the APF algorithm. This method can effectively solve the trajectory planning problems of mobile robots in environments with unknown obstacles and dynamic disturbances. Through these studies, we have made some progress in the field of trajectory planning of mobile robots and provided effective technical support to improve the autonomy and adaptability of mobile robots.