TY - CHAP
T1 - Multi-goal motion planning of an autonomous robot in unknown environments by an ant colony optimization approach
AU - Luo, Chaomin
AU - Mo, Hongwei
AU - Shen, Furao
AU - Zhao, Wenbing
PY - 2016/1/1
Y1 - 2016/1/1
N2 - An ant colony optimization (ACO) approach is proposed in this paper for real-time concurrent map building and navigation for multiple goals purpose. In real world applications such as rescue robots, and service robots, an autonomous mobile robot needs to reach multiple goals with the shortest path that, in this paper, is capable of being implemented by an ACO method with minimized overall distance. Once a global path is planned, a foraging-enabled trail is created to guide the robot to the multiple goals. A histogram-based local navigation algorithm is employed locally for obstacle avoidance along the trail planned by the global path planner. A re-planning-based algorithm aims to generate path while a mobile robot explores through a terrain with map building in unknown environments. In this paper, simulation results demonstrate that the real-time concurrent mapping and multi-goal navigation of an autonomous robot is successfully performed under unknown environments.
AB - An ant colony optimization (ACO) approach is proposed in this paper for real-time concurrent map building and navigation for multiple goals purpose. In real world applications such as rescue robots, and service robots, an autonomous mobile robot needs to reach multiple goals with the shortest path that, in this paper, is capable of being implemented by an ACO method with minimized overall distance. Once a global path is planned, a foraging-enabled trail is created to guide the robot to the multiple goals. A histogram-based local navigation algorithm is employed locally for obstacle avoidance along the trail planned by the global path planner. A re-planning-based algorithm aims to generate path while a mobile robot explores through a terrain with map building in unknown environments. In this paper, simulation results demonstrate that the real-time concurrent mapping and multi-goal navigation of an autonomous robot is successfully performed under unknown environments.
KW - Ant colony optimization
KW - Autonomous robot
KW - Mapping
KW - Multi-goal motion planning
KW - Unknown environments
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85010194166&origin=inward
UR - https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85010194166&origin=inward
U2 - 10.1007/978-3-319-41009-8_56
DO - 10.1007/978-3-319-41009-8_56
M3 - Chapter
VL - 9713 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 519
EP - 527
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PB - Springer [email protected]
CY - deu
T2 - International Conference on Swarm Intelligence
Y2 - 1 January 2016
ER -