{"title":"A Path Planning System based on 3D Occlusion Detection for Lunar Exploration Rovers","authors":"A. Mora, K. Nagatani, Kazuya Yoshida, M. Chacin","doi":"10.1109/SMC-IT.2009.59","DOIUrl":null,"url":null,"abstract":"In this paper, the authors present a path planing system for autonomous navigation of lunar/planetary rover. In the path planner, candidate paths are generated and evaluated by multiple criteria including occlusion index, terrain roughness/inclination indices. The proposed system considers the occlusion effect produced by obstacles present in the inspected environment and the features of the environment itself. An algorithm that computes the next sensing position within the map is introduced as part of the system presented. The different components of the system and their interactions are explained thoroughly. Simulation and experimental results where the proposed system is implemented are presented.","PeriodicalId":422009,"journal":{"name":"2009 Third IEEE International Conference on Space Mission Challenges for Information Technology","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Third IEEE International Conference on Space Mission Challenges for Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMC-IT.2009.59","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In this paper, the authors present a path planing system for autonomous navigation of lunar/planetary rover. In the path planner, candidate paths are generated and evaluated by multiple criteria including occlusion index, terrain roughness/inclination indices. The proposed system considers the occlusion effect produced by obstacles present in the inspected environment and the features of the environment itself. An algorithm that computes the next sensing position within the map is introduced as part of the system presented. The different components of the system and their interactions are explained thoroughly. Simulation and experimental results where the proposed system is implemented are presented.