Experimental Validation for CRFNFP Algorithm

In 2010,we proposed CRFNFP[1] algorithm to enhance long-range terrain perception for outdoor robots through the integration of both appearance features and spatial contexts. And our preliminary simulation results indicated the superiority of CRFNFP over other existing approaches in terms of accuracy, robustness and adaptability to dynamic unstructured outdoor environments. In this paper, we further study on the comparison experiments for navigation behaviors of robotic systems with different scene perception algorithms in real outdoor scenes. We implemented 3 robotic systems and repeated the running jobs under various conditions. We also defined 3 creterion to facilitate comparison for all systems: Obstacle Response Distance (ORD), Time to Finish Job (TFJ), Distance of the Whole Run (DWR). The comparative experiments indicate that, the CRFNFP-based navigating system outperforms traditional local-map-based navigating systems in terms of all criterion. And the results also show that the CRFNFP algorithm does enhance the long-range perception for mobile robots and helps planning more efficient paths for the navigation.

@article{Mingjun2012,
  title     = {Experimental Validation for CRFNFP Algorithm},
  journal   = {International Journal of Advanced Research in Artificial Intelligence},
  volume    = {1},
  number    = {2},
  year      = {2012},
  publisher = {The Science and Information Organization},
  author    = {Wang Mingjun and Yi Xinhua and Wang Xuefeng and Tu Jun},
  doi       = {10.14569/IJARAI.2012.010203},
  url       = {https://doi.org/10.14569/IJARAI.2012.010203}
}