Abstract
The known algorithms for planning the trajectory of movement of mobile robots in an unknown environment have high computational complexity or do not allow finding the trajectory that is optimal along the length of the path, while maintaining a safe distance from obstacles. The aim of the work is to increase the efficiency of solving the problem of planning the trajectory of movement of mobile robots from the initial position to the final position in an unknown environment with obstacles, taking into account the limited capabilities (sensory and computational) of mobile robots. The solution to this problem was carried out on the basis of step-by-step optimization of the current position of the robot relative to a given target. The proposed method analyzes the possibility of a robot moving in directions determined by means of analytical geometry based on measurements of on-board distance sensors. An element of scientific novelty is the procedure for calculating trajectory segments based on the choice of an intermediate state and correcting the trajectory taking into account the measurements of the on-board distance sensors of the mobile robot. The proposed method makes it possible to search for the trajectory of a mobile robot in an unknown environment while ensuring a given distance to obstacles. The use of the presented algorithm allows the robot to maintain a high efficiency of the task while functioning in conditions of information deficiency. The reliability of the results was confirmed in the course of software simulation. The solution of the problem, taking into account these features, made it possible to reduce the computational complexity of the method, as well as to remove restrictions on the use of trajectory planning algorithms for mobile robots with low-performance on-board sensors and computing devices. The presented algorithm is implemented in the form of software in the Python programming language, which can be used to simulate autonomous control systems for mobile robots.
Highlights
Robots and robotic systems (RS) are widely used in many areas of human activity
Based on the analysis of research works [1,2,3,4,5], one of the key problems arising during the operation of mobile robots (MR) in an unknown environment is the planning of safe trajectories of movement, allowing to build accident-free routes close to optimal
The presented method allows planning the trajectory of the MR in an unknown closed environment with obstacles, taking into account the limited performance of the on-board sensors and computing devices of the MR
Summary
Robots and robotic systems (RS) are widely used in many areas of human activity. This is because these systems allow automating a number of laborious and routine tasks: monitoring and response to emergencies, rescue operations, underwater research, agricultural work, reconnaissance operations, and many others. The approaches used to solve the problem of planning the trajectory of movement can be conditionally divided into 2 main groups: 1) classical search algorithms - Dijkstra's algorithm, depth-first search, A*, graph search methods [6,7,8]; 2) intelligent algorithms - artificial neural networks, fuzzy and genetic algorithms, the main advantage of which is the speed of calculation with a moderate load on the on-board computing devices of robots [9,10,11]
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call