Object-Based Reliable Visual Navigation for Mobile Robot

doi:10.3390/s22062387

	Object-Based Reliable Visual Navigation for Mobile Robot
	Wang, Fan 1,2; Zhang, Chaofan 1; Zhang, Wen 1; Fang, Cuiyun 1,2; Xia, Yingwei 1; Liu, Yong 1; Dong, Hao 3
刊名	SENSORS
	2022-03-01
卷号	22
关键词	topological path planning visual navigation object-level topological semantic map Bernstein polynomial
DOI	10.3390/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.
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关键词	FAST-MARCHING-METHOD ; SIMULTANEOUS LOCALIZATION ; TRAJECTORY GENERATION ; PATH ; SLAM ; FUTURE ; ROBUST
WOS研究方向	Chemistry ; Engineering ; Instruments & Instrumentation
语种	英语
出版者	MDPI
WOS记录号	WOS:000774243100001
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
内容类型	期刊论文
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.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Hefei Inst Phys Sci, Hefei 230031, Peoples R China 2.Univ Sci & Technol China, Grad Sch, Sci Isl Branch, Hefei 230026, Peoples R China 3.China Natl Tobacco Qual Supervis Test Ctr, Zhengzhou 450001, 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).