Here we present a novel bio-inspired optic flow (OF) sensor and its application to visual guidance and odometry on a low-cost car-like robot called BioCarBot. The minimalistic OF sensor was robust to high-dynamic-range lighting conditions and to various visual patterns encountered thanks to its MAPIX auto-adaptive pixels and the new cross-correlation OF algorithm implemented. The low-cost car-like robot estimated its velocity and steering angle, and therefore its position and orientation, via an extended Kalman filter (EKF) using only two downward-facing OF sensors and the Ackerman steering model. Indoor and outdoor experiments were carried out in which the robot was driven in the closed-loop mode based on the velocity and steering angle estimates. The experimental results obtained show that our novel OF sensor can deliver high-frequency measurements ([Formula: see text]) in a wide OF range (1.5-[Formula: see text]) and in a 7-decade high-dynamic light level range. The OF resolution was constant and could be adjusted as required (up to [Formula: see text]), and the OF precision obtained was relatively high (standard deviation of [Formula: see text] with an average OF of [Formula: see text], under the most demanding lighting conditions). An EKF-based algorithm gave the robot's position and orientation with a relatively high accuracy (maximum errors outdoors at a very low light level: [Formula: see text] and [Formula: see text] over about [Formula: see text] and [Formula: see text]) despite the low-resolution control systems of the steering servo and the DC motor, as well as a simplified model identification and calibration. Finally, the minimalistic OF-based odometry results were compared to those obtained using measurements based on an inertial measurement unit (IMU) and a motor's speed sensor.
In this paper, we present (i) a novel bio-inspired 1-D OF sensor which is robust to high-dynamic-range lighting conditions and independent of the visual patterns encountered, and (ii) a low-cost car-like robot called BioCarBot, which estimates its velocity and steering angle by means of an Extended Kalman Filer (EKF) using only the OF measurements delivered by two downward-facing sensors of this kind. Indoor experiments were carried out, in which the robot was driven in the closed-loop mode, using a proportional integral (PI) controller based on the velocity and steering angle estimates. The results presented here show that our novel OF sensor can deliver a wide range of high-frequency (333 Hz) OF measurements (from 1 to 10 rad s ) with a relatively high resolution (up to 0.05 rad s ) in a 5-decade high-dynamic range of light levels. Neither the refresh rate nor the resolution of the OF sensors presented here depended on either the visual patterns or the lighting conditions, and could be theoretically set at whatever value required.
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