Bio-Inspired Obstacle Avoidance using Wavelet-Based Element Analysis

The paper proposes a bio-inspired approach to the obstacle avoidance problem using analytic wavelet transform to extract perception cues for the reactive control. The small and large scale environment features are perceived using laser scans. Wavelets are then used as the bases of projection of the spatial signals, in order to decompose and observe the environment features of interest. The wavelet-based element analysis is leveraged for this purpose, using Morse wavelets as the analytic wavelet bases. The inspiration of the approach is derived from the principle of sensorimotor convergence that has been studied in many small living organisms. A steering potential function, based on a human walking model, is finally used to close the control loop. The safety of the method is analyzed by computing appropriate barrier certificates. The algorithm is programmed and released as a ROS/C++ package and is thoroughly tested using physical hardware experiments.