@Article{martinez:isj:2020,
  author    = {Martinez, Rodriguez, A. Eder and Caron, Guillaume and P{\'e}gard, Claude and Lara-Alabazares, David},
  title     = {Photometric-Planner for Visual Path Following},
  journal   = {IEEE Sensors Journal},
  year      = {2021},
  volume    = {21},
  number    = {10},
  pages     = {11310--11317},
  month     = {September},
  doi       = {10.1109/JSEN.2020.3027848},
  url       = {https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\&arnumber=9210085},
  keywords  = {Visualization, Navigation, Robot sensing systems, Autonomous robots, Visual perception},
  abstract  = {Robotic navigation is the aspect of cognition related to robot robust mobility, combining perception, some knowledge on the environment and a set of goal poses to reliably control the robot during a mission that involves displacement. Vision-based autonomous navigation is an instantiation of the latter discipline where visual perception is used to control the robot and to represent the environment. This paper presents a vision-based navigation system that uses its onboard camera to navigate and a visual path that represents the scene with a set of images. Being a memory-based system, the navigation is conceived as a concatenation of positioning tasks in the visual servoing scheme. The novelty on the proposed system relies on the generation of the images that compose the visual path which are rendered from a preobtained model of the scene. The experiments that evaluate the performance of the system are conducted over three different scenes, contemplating indoor and outdoor environments, and using a commercial Unmanned Aerial Vehicle as testbed.},
  publisher = {IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC},
  address   = {445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA}
}