Real-time obstacle detection for legged robots using the Kinect sensor

Autonomous navigation of legged robots in complex environments poses a great deal of challenges compared with ground vehicles because of their different terrain traverse capabilities. An obstacle for vehicles may be traversable for legged robots. This paper proposes a real-time obstacle detection algorithm for legged robots using the Microsoft Kinect sensor. First, the elevation map of a reference grid is calculated. Then an obstacle definition for legged robots is proposed, which makes it possible for a legged robot to discriminate traversable areas from non-traversable areas. To reduce computational cost, sometimes, efficient judging rules are developed to identify obstacles. A spiral search strategy is proposed to find the most ground-like point as the starting point for graph-based traversal. Breadth-First-Traversal of the graph is used to label all traversable areas connecting to the starting point. Experimental results demonstrate that our algorithm is reliable and efficient. The proposed algorithm can be employed in real-time obstacle detection for legged robots in complex environments.