Vision based Environment Mapping by Network Connected Multi-robotic System

M. Shuja Ahmed, Reza Saatchi, Fabio Caparrelli

2013

Abstract

The conventional environment mapping solutions are computationally very expensive and cannot effectively be used in multi-robotic environment, where small size robots with limited memory and processing resources are used. This study provides an environment mapping solution in which a group of small size robots extract simple distance vector features from the on-board camera images. The robots share these features between them using a wireless communication network setup in infrastructure mode. For mapping the distance vector features on a global map and to show a collective map building operation, the robots needed their accurate location and heading information. The robots location and heading information is computed using two ceiling mounted cameras, which collective localises the robots. Experimental results show that the proposed method provides the required environmental map which can facilitate the robot navigation operation in the environment. It was observed that, using the proposed approach, the near by object boundaries can be mapped with higher accuracy comparatively the far lying objects.

References

  1. Ahmed, M., Saatchi, R., and Caparrelli, F. (2012a). Vision based object recognition and localisation by a wireless connected distributed robotic systems. In Electronic Letters on Computer Vision and Image Analysis, Vol.11, No.1, Pages 54-67.
  2. Ahmed, M., Saatchi, R., and Caparrelli, F. (2012b). Vision based obstacle avoidance and odometery for swarms of small size robots. In Proceedings of 2nd International Conference on Pervasive and Embedded Computing and Communication Systems, Pages 115-122.
  3. Biber, P., Andreasson, H., Duckett, T., and Schilling, A. (2004). 3d modeling of indoor environments by a mobile robot with a laser scanner and panoramic camera. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Vol.4, Pages 3430-3435.
  4. Howard, A. (2004). Multi-robot mapping using manifold representations. In IEEE International Conference on Robotics and Automation(ICRA), Vol.4, Pages 4198- 4203.
  5. Kwon, Y. and Lee, J. (1999). A stochastic map building method for mobile robot using 2-d laser range finder. In Journal of Autonomous Robots, Vol.7 No.2, Pages 187-200.
  6. Latecki, L., Lakaemper, R., and Adluru, N. (2007). Multi robot mapping using force field simulation. In Journal of Field Robotics, Vol.24, Pages 747-762.
  7. Leon, A., Barea, R., Bergasa, L., Lopez, E., Ocana, E., and Schleicher, D. (2009). Multi-robot slam and map merging. In Journal of Phyical Agents, Vol.3, Pages 171-176.
  8. REPLICATOR (2008). Robotic evolutionary selfprogramming and self-assembling organisms. In EU-FP7 Research Project REPLICATOR. URL: http://symbrion.org/.
  9. Shen, Y., Liu, J., and Xin, D. (2008). Environment map building and localization for robot navigation based on image sequences. In Journal of Zhejiang University ScienceA, Vol.9, No.4, Pages 489-499.
  10. Surveyor-Corporation (2012). Surveyor srv-1 open source mobile robot. In www.surveyor.com/.
  11. SYMBRION (2008). Symbiotic evolutionary robot organisms. In European Communities 7th Framework Programme Project No FP7-ICT-2007.8.2. URL: http://symbrion.org/.
  12. Wolf, D. and Hata, A. (2009). Outdoor mapping using mobile robots and laser range finders. In Conference of Electronics, Robotics and Automotive Mechanics, Pages 209-214.
Download


Paper Citation


in Harvard Style

Ahmed M., Saatchi R. and Caparrelli F. (2013). Vision based Environment Mapping by Network Connected Multi-robotic System . In Proceedings of the 3rd International Conference on Pervasive Embedded Computing and Communication Systems - Volume 1: PECCS, ISBN 978-989-8565-43-3, pages 49-54. DOI: 10.5220/0004314600490054


in Bibtex Style

@conference{peccs13,
author={M. Shuja Ahmed and Reza Saatchi and Fabio Caparrelli},
title={Vision based Environment Mapping by Network Connected Multi-robotic System},
booktitle={Proceedings of the 3rd International Conference on Pervasive Embedded Computing and Communication Systems - Volume 1: PECCS,},
year={2013},
pages={49-54},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004314600490054},
isbn={978-989-8565-43-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Conference on Pervasive Embedded Computing and Communication Systems - Volume 1: PECCS,
TI - Vision based Environment Mapping by Network Connected Multi-robotic System
SN - 978-989-8565-43-3
AU - Ahmed M.
AU - Saatchi R.
AU - Caparrelli F.
PY - 2013
SP - 49
EP - 54
DO - 10.5220/0004314600490054