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Author:

Jia, Songmin (Jia, Songmin.) (Scholars:贾松敏) | Guo, Bing (Guo, Bing.) | Li, Xiuzhi (Li, Xiuzhi.) | Wang, Ke (Wang, Ke.) | Li, Yuchen (Li, Yuchen.)

Indexed by:

CPCI-S

Abstract:

In this paper, we presents an efficient simultaneous localization and mapping (SLAM) technique in multi-obstacle environment for indoor mobile robot navigation based on Laser Range Finder. We use Rao-Blackwellized Particle Filter (RBPF) to localize mobile robot and use Vector Field Histogram (VFH) for obstacle avoidance. In our system, Robot Technology Middleware (RTM) was used. By using RTM, we can develop functional elements as "RT software components" that can be implemented by different programming languages, run in different operating system, or connected in different networks to inter-operate. Based on RTM, we developed LRF data getting component, mobile robot control component, VFH component, RBPF component and GUI component. This paper describes the architecture of the proposed system and gives some experimental results.

Keyword:

SLAM VFH mobile robot Laser Range Finder Map building

Author Community:

  • [ 1 ] [Jia, Songmin]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing, Peoples R China
  • [ 2 ] [Guo, Bing]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing, Peoples R China
  • [ 3 ] [Li, Xiuzhi]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing, Peoples R China
  • [ 4 ] [Wang, Ke]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing, Peoples R China
  • [ 5 ] [Li, Yuchen]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing, Peoples R China

Reprint Author's Address:

  • 贾松敏

    [Jia, Songmin]Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing, Peoples R China

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Source :

PROCEEDING OF THE IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION

Year: 2012

Page: 271-276

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 13

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