中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 合肥物质科学研究院
  3. 中国科学院合肥物质科学研究院
Object-Based Reliable Visual Navigation for Mobile Robot

文献类型：期刊论文

作者Wang, Fan2,3; Zhang, Chaofan3; Zhang, Wen3; Fang, Cuiyun2,3; Xia, Yingwei3; Liu, Yong3; Dong, Hao1
刊名SENSORS
出版日期2022-03-01
卷号22
关键词topological path planning visual navigation object-level topological semantic map Bernstein polynomial
DOI10.3390/s22062387
通讯作者Zhang, Chaofan(zcfan@aiofm.ac.cn) ; Zhang, Wen(zhangwen@aiofm.ac.cn)
英文摘要Visual navigation is of vital importance for autonomous mobile robots. Most existing practical perception-aware based visual navigation methods generally require prior-constructed precise metric maps, and learning-based methods rely on large training to improve their generality. To improve the reliability of visual navigation, in this paper, we propose a novel object-level topological visual navigation method. Firstly, a lightweight object-level topological semantic map is constructed to release the dependence on the precise metric map, where the semantic associations between objects are stored via graph memory and topological organization is performed. Then, we propose an object-based heuristic graph search method to select the global topological path with the optimal and shortest characteristics. Furthermore, to reduce the global cumulative error, a global path segmentation strategy is proposed to divide the global topological path on the basis of active visual perception and object guidance. Finally, to achieve adaptive smooth trajectory generation, a Bernstein polynomial-based smooth trajectory refinement method is proposed by transforming trajectory generation into a nonlinear planning problem, achieving smooth multi-segment continuous navigation. Experimental results demonstrate the feasibility and efficiency of our method on both simulation and real-world scenarios. The proposed method also obtains better navigation success rate (SR) and success weighted by inverse path length (SPL) than the state-of-the-art methods.
WOS关键词FAST-MARCHING-METHOD ; SIMULTANEOUS LOCALIZATION ; TRAJECTORY GENERATION ; PATH ; SLAM ; FUTURE ; ROBUST
资助项目Joint fund of Science and Technology Department of Liaoning Province ; State Key Laboratory of Robotics, China[2020-KF-22-16] ; Key Research and Development Program of Anhui Province of China[202104a05020043] ; Open Projects Program of National Laboratory of Pattern Recognition[202100040]
WOS研究方向Chemistry ; Engineering ; Instruments & Instrumentation
语种英语
WOS记录号WOS:000774243100001
出版者MDPI
资助机构Joint fund of Science and Technology Department of Liaoning Province ; State Key Laboratory of Robotics, China ; Key Research and Development Program of Anhui Province of China ; Open Projects Program of National Laboratory of Pattern Recognition
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/128283]  
专题中国科学院合肥物质科学研究院
通讯作者Zhang, Chaofan; Zhang, Wen
作者单位1.China Natl Tobacco Qual Supervis Test Ctr, Zhengzhou 450001, Peoples R China
2.Univ Sci & Technol China, Grad Sch, Sci Isl Branch, Hefei 230026, Peoples R China
3.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Hefei Inst Phys Sci, Hefei 230031, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Fan,Zhang, Chaofan,Zhang, Wen,et al. Object-Based Reliable Visual Navigation for Mobile Robot[J]. SENSORS,2022,22.
APA Wang, Fan.,Zhang, Chaofan.,Zhang, Wen.,Fang, Cuiyun.,Xia, Yingwei.,...&Dong, Hao.(2022).Object-Based Reliable Visual Navigation for Mobile Robot.SENSORS,22.
MLA Wang, Fan,et al."Object-Based Reliable Visual Navigation for Mobile Robot".SENSORS 22(2022).

入库方式： OAI收割

来源：合肥物质科学研究院

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。