Dept. of Comput. Sci. & Inf. Eng., National Taiwan Univ.Chang, Tsai-YuTsai-YuChangKuo, Szu-WenSzu-WenKuoYUNG-JEN HSU2007-04-192018-07-052007-04-192018-07-051994-0921530858http://ntur.lib.ntu.edu.tw//handle/246246/2007041910032476https://www.scopus.com/inward/record.uri?eid=2-s2.0-85025222273&doi=10.1109%2fIROS.1994.407376&partnerID=40&md5=7a9f337f09730b0e838b1287056eb69bThis paper presents an implemented navigation system for mobile robots in dynamic environments. In order to take advantage of existing knowledge of the world and to deal with unknown obstacles in realtime, our system divides motion planning into global path planning and local reactive navigation. The former uses genetic algorithm methods to find a collision-free path; the latter is implemented using neural network techniques to track the path generated by the global planner while avoiding unknown obstacles on the way. As a result, the system can adapt to dynamic environmental changes. Our experiments, both in simulation and on a real robot, showed that the system can find a reasonably good free path in a fraction of the time necessary to find an optimal free path, and it can effectively achieve its goal configurations without collision. © 1994 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.application/pdf569012 bytesapplication/pdfen-US[SDGs]SDG11Genetic algorithms; Motion planning; Navigation systems; Algorithm methods; Collision-free paths; Dynamic environments; Free path; Global path planning; Motion-planning; Neural network techniques; Reactive navigation; Real- time; Two phase; Mobile robotsconference paper10.1109/IROS.1994.4073762-s2.0-85025222273http://ntur.lib.ntu.edu.tw/bitstream/246246/2007041910032476/1/00407376.pdf