A Bio-inspired Collision Avoidance Model Based on Spatial Information Derived from Motion Detectors Leads to Common Routes
Fig 1
Sketch of the algorithm from motion to CAD.
1) The motion of the agent consists of a series of translations in the null elevation plane. 2) Optic-flow fields along the trajectory contain FOEs and FOCs. 3) The time-integrated optic flow squared does not contain FOC and FOE. Inset is a 10× zoom at the mean motion direction of the agent. 4) Nearness map computed from time-integrated optic flow squared. 5) Nearness map averaged along the elevation. 6) Computation of the COMANV. Blue: representation of the vertically integrated nearness map in polar coordinates. Red: vectorial sum of the vertically integrated nearness vectors (COMANV). Green: vector directed opposite to the COMANV.