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Abstract

This disclosure relates generally to method and system to detect and estimate dynamic obstacles using RGBD sensors for robot navigation. Obstacle detection and tracking tasks with efficient processing of depth images becomes complex in dynamic and cluttered environments. The method detects one or more obstacles being identified in the one or more depth images in two dimensional space using the depth map captured using a RGBD sensor configured to a mobile robot. Further, a restricted v-depth map is computed between specified columns taken from the width of each dynamic obstacle of the u-depth map and within the depth range derived from the u-depth map. The one or more dynamic obstacles are tracked by matching segments of subsequent depth images to predict future position in the region of the monitoring environment by computing a closeness signature. The method evaluates correctness with open data sequence and real world data.

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First Claim