Performance Measurement of Energy Optimal Path Finding for Waste Collection Robot Using ACO Algorithm

Abstract

Indoor waste collection that utilizes mobile robots can solve the labor cost and manpower shortage but has the problem of limited energy resources, making it difficult to operate for long periods of time. Therefore, it is important to reduce the energy consumption for efficient waste collection. The waste collection robot can be modeled as a Capacitated Vehicle Routing Problem (CVRP), where heuristics algorithms can be deployed to search for the most energy-efficient path. This paper proposes the Ant Colony Optimization (ACO) algorithm for finding the optimal path of the waste collection robot. Energy consumption of the robot depends not only on the travel path but also on the weight of the waste it carries. Therefore, the proposed ACO algorithm utilizes the path distance and waste weight as the visibility. The travel distance and energy consumption are also used to determine the updated pheromone. Whereas the conventional and adapted ACO algorithms use only either the path distance or the waste weight as the visibility, respectively. The simulation experiments are conducted to compare the travel distance and the energy consumption that the waste collection robot takes by using the conventional, adapted, and proposed ACO algorithms. In the simulation experiments, the number of nodes, the waste weight, and the carrying capacity are used as parameters to verify the performance under the determined environment. The simulation results express that the proposed ACO algorithm provides a better energy optimal path in terms of travel distance and energy consumption than the conventional and adapted ACO algorithms.

Multi-objective path planning for mobile robot based on ACO -APF fusion algorithm

“…In APF method, the total potential field 𝑈𝑈 consists of attractive field 𝑈𝑈 𝑎𝑎𝑎𝑎𝑎𝑎 and repulsive field 𝑈𝑈 𝑟𝑟𝑟𝑟𝑟𝑟 , which could be defined as in the formula (4). The 𝑈𝑈 𝑎𝑎𝑎𝑎𝑎𝑎 is show in the formula (5),the 𝑈𝑈 𝑟𝑟𝑟𝑟𝑟𝑟 is show in the formula (6).…”

“…Alhenawi Esra' A, et al [5] proposed a parallel ant colony optimization algorithm to find the shortest climbing path, which guarantees the safety of the chosen path by introducing some constraint conditions considering the safe slope of the path. Tomitagawa Koki, et al [6] proposed an ant colony algorithm to find the optimal path of a garbage collection robot. Travel distance and energy expenditure are also used to determine the updated pheromone.…”

Minimum Energy Utilization Strategy for Fleet of Autonomous Robots in Urban Waste Management

“…For various autonomous service robots in the field of waste management, the biggest challenge lies not only in the the automation of the process, but also in the operational management, in the form of route planning for the Service Event Area [8,12,13]. Optimized route planning means the shortest path and least possible energy consumption for the overall waste-management service [14].…”