Home > Papers from 2015 > A new view-based navigation algorithm

A new view-based navigation algorithm

Despite the impressive performance of modern state of the art visual navigation algorithms, there still seems to be a role for insect-inspired algorithms in robotics. This is especially true for lightweight air vehicles. Denuelle et al propose a new view-based algorithm for place homing on a quad-copter style platform, where it is proposed the algorithm would be useful in the control of hover. For homing, the agent uses three difference images in order to create a difference frame of reference. By storing image differences (i.e. current image compared to image from the goal location) for non-colinear points surrounding the goal, the agent can build a frame of reference such that when trying to home, the current difference image can be used to localise oneself without the need for exploratory movements. In general terms the algorithm is reminiscent of gradient models which are proposed for true navigation in vertebrates. In more niche terms, the model reminds me of Ralf Moller’s MFDID models, but where the sampling around the goal in the learning phase allows the agent to tune the computations to local natural image statistics and therefore allows estimates of distance to the goal to be gained.

Denuelle, A., Thurrowgood, S., Kendoul, F., & Srinivasan, M. V. (2015, February). A view-based method for local homing of unmanned rotorcraft. In Automation, Robotics and Applications (ICARA), 2015 6th International Conference on (pp. 443-449). IEEE.

Categories: Papers from 2015
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