TY - JOUR
T1 - Ant colony test center for planning autonomous mobile robot navigation
AU - Montiel-Ross, Oscar
AU - Sepúlveda, Roberto
AU - Castillo, Oscar
AU - Melin, Patricia
PY - 2013/6
Y1 - 2013/6
N2 - This paper presents the navigation software called Ant Colony Test Center designed to teach the different stages involved in mobile robotics. The navigation problem consists of the four subproblems: world perception, path planning, path generation, and path tracking. This software based on ant colonies has two operational modes: virtual and on-line. In virtual mode, is able to achieve path generation, path planning and virtual path tracking at once, since the virtual mobile robots "ants" searches for the objective point generating feasible paths, then generate a set of subgoals to obtain the optimal path, since the optimal path was obtained using a cost function that considers the robot architecture, the optimal trajectory for the robot also is obtained. In on-line mode, the robot is able to sense the world using stereoscopic vision, the map is updated using epipolar geometry, and the on-line navigation problem is handled similar to the virtual mode. The software has many educational skills, since students can learn about path generation, optimal planning and path tracking using the heuristic methodology known as Ant Colony Optimization that recently has had good acceptance for solving discrete optimization planning problems. The platform is also a good tool to learn about stereoscopic vision and epipolar geometry that is one of the best sensing methods in mobile robotics.
AB - This paper presents the navigation software called Ant Colony Test Center designed to teach the different stages involved in mobile robotics. The navigation problem consists of the four subproblems: world perception, path planning, path generation, and path tracking. This software based on ant colonies has two operational modes: virtual and on-line. In virtual mode, is able to achieve path generation, path planning and virtual path tracking at once, since the virtual mobile robots "ants" searches for the objective point generating feasible paths, then generate a set of subgoals to obtain the optimal path, since the optimal path was obtained using a cost function that considers the robot architecture, the optimal trajectory for the robot also is obtained. In on-line mode, the robot is able to sense the world using stereoscopic vision, the map is updated using epipolar geometry, and the on-line navigation problem is handled similar to the virtual mode. The software has many educational skills, since students can learn about path generation, optimal planning and path tracking using the heuristic methodology known as Ant Colony Optimization that recently has had good acceptance for solving discrete optimization planning problems. The platform is also a good tool to learn about stereoscopic vision and epipolar geometry that is one of the best sensing methods in mobile robotics.
KW - Ant Colony Optimization
KW - Fuzzy Logic
KW - Simple Tuning Algorithm
KW - autonomous mobile robot navigation
KW - path planning
UR - http://www.scopus.com/inward/record.url?scp=84876138034&partnerID=8YFLogxK
U2 - 10.1002/cae.20463
DO - 10.1002/cae.20463
M3 - Artículo
SN - 1061-3773
VL - 21
SP - 214
EP - 229
JO - Computer Applications in Engineering Education
JF - Computer Applications in Engineering Education
IS - 2
ER -