Keywords: vehicle routing, planar graph, heuristic algorithm, optimization, obstacle avoidance, traveling salesman problem
UDC 004.896
DOI: 10.26102/2310-6018/2026.59.8.004
One of the urgent tasks is ground-based monitoring of the condition of various facilities. It may be necessary not only in industrial enterprises, but also in agriculture (inspection of orchards), medicine (monitoring the condition of patients in infectious diseases departments), and emergency situations. In these situations, it is not possible to place sensors and smart cameras in fixed locations. In addition, there are situations when monitoring goals are set immediately before it is carried out. Another urgent task is to build a robot's path, taking into account the presence of obstacles. This article discusses an algorithm for constructing the shortest route for monitoring at a finite set of points by a ground robot, taking into account obstacles. The task of determining the trajectory of a robot is formulated as a vehicle routing task. Data on the coordinates of the robot and the location of monitoring points is stored as a weighted planar graph using a list of edges. The article proposes the algorithm SearchWithObstacles, using function SPPA (Shortest Path with Precautionary Avoidance), which is based on the nearest neighbor method and solves the problem in polynomial time. The algorithm is compared with known approaches and the advantages and disadvantages of the proposed algorithm are discussed.
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Keywords: vehicle routing, planar graph, heuristic algorithm, optimization, obstacle avoidance, traveling salesman problem
For citation: Makarovskikh T.A., Sallam M.E. An algorithm for determining the optimal route of the robot for monitoring objects, taking into account obstacles. Modeling, Optimization and Information Technology. 2026;14(8). URL: https://moitvivt.ru/ru/journal/article?id=2427 DOI: 10.26102/2310-6018/2026.59.8.004 (In Russ).
© Makarovskikh T.A., Sallam M.E. Статья опубликована на условиях лицензии Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NS 4.0)Received 30.05.2026
Revised 06.08.2026
Accepted 13.08.2026