An Effective Path Planning Method Based on VDWF-MOIA for Multi-Robot Patrolling in Expo Parks DOI Open Access
Tianyi Guo, Li Huang, Hua Han

et al.

Electronics, Journal Year: 2025, Volume and Issue: 14(6), P. 1222 - 1222

Published: March 20, 2025

Expo parks are characterized by dense crowds and a high risk of accidents. A multi-robot patrolling system equipped with multiple sensors can provide personalized services to visitors quickly locate emergencies, effectively accelerating response times. This study focuses on developing efficient strategies for systems. In expo parks, this requires solving the traveling salesman problem (MTSP) addressing obstacle avoidance in static environments. The main challenge is plan paths allocate tasks while avoiding collisions balancing workloads. Traditional methods often struggle optimize task allocation path planning at same time. lead an unbalanced distribution patrol tasks. Some robots may have too much workload, others not fully utilized. addition, poor increase total length reduce overall efficiency. It also affect coordination system, limiting its scalability applicability. To solve these problems, paper proposes multi-objective immune optimization algorithm based Van der Waals force mechanism (VDWF-MOIA). introduces innovative double-antibody coding scheme that adapts well environments obstacles, making it easier represent solutions more diversely. has two levels. At lower level, cost matrix vector rotation-angle-based (PCM-VRAOA) calculates costs detour nodes. reduces identifies optimal paths, facilitating collaborative subsequent allocation. higher crossover operator inspired enhances solution diversity convergence enabling effective between antibody segments, resulting offspring. proposed improves performance enhancing diversity, speeding up convergence, reducing computational costs. Compared other algorithms, experiments test datasets environment show VDWF-MOIA performs better terms length, load metrics, hypervolume (HV) indicator.

Language: Английский

An Effective Path Planning Method Based on VDWF-MOIA for Multi-Robot Patrolling in Expo Parks DOI Open Access
Tianyi Guo, Li Huang, Hua Han

et al.

Electronics, Journal Year: 2025, Volume and Issue: 14(6), P. 1222 - 1222

Published: March 20, 2025

Expo parks are characterized by dense crowds and a high risk of accidents. A multi-robot patrolling system equipped with multiple sensors can provide personalized services to visitors quickly locate emergencies, effectively accelerating response times. This study focuses on developing efficient strategies for systems. In expo parks, this requires solving the traveling salesman problem (MTSP) addressing obstacle avoidance in static environments. The main challenge is plan paths allocate tasks while avoiding collisions balancing workloads. Traditional methods often struggle optimize task allocation path planning at same time. lead an unbalanced distribution patrol tasks. Some robots may have too much workload, others not fully utilized. addition, poor increase total length reduce overall efficiency. It also affect coordination system, limiting its scalability applicability. To solve these problems, paper proposes multi-objective immune optimization algorithm based Van der Waals force mechanism (VDWF-MOIA). introduces innovative double-antibody coding scheme that adapts well environments obstacles, making it easier represent solutions more diversely. has two levels. At lower level, cost matrix vector rotation-angle-based (PCM-VRAOA) calculates costs detour nodes. reduces identifies optimal paths, facilitating collaborative subsequent allocation. higher crossover operator inspired enhances solution diversity convergence enabling effective between antibody segments, resulting offspring. proposed improves performance enhancing diversity, speeding up convergence, reducing computational costs. Compared other algorithms, experiments test datasets environment show VDWF-MOIA performs better terms length, load metrics, hypervolume (HV) indicator.

Language: Английский

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