Toward safe navigation in urban environments

This paper presents a complete system for autonomous navigation of a mobile robot in urban environments. An urban environment is defined as one having hard surface and comprising curbs, ramps, and obstacles. The robot is required to traverse flat ground surfaces and ramps, but avoid curbs and obstacles. The system employs a 2-D laser rangefinder for terrain mapping. In order to filter erroneous sensor data (mixed pixels and noises), an Extended Kalman Filter (EKF) is used to segment the laser range data into straight-line segments and isolated points. The isolated points are then compared with those points at their neighboring straight-line segments to detect discontinuity in received energy (called reflectivity value in this work). The points exhibiting discontinuity of reflectivity are identified as erroneous data and removed. A so-called “Polar Traversability Index” measure is proposed to evaluate terrain traversal property. A PTI dictates the level of difficulty for a robot to move along the corresponding direction. It enables the robot to traverse wheelchair ramps and avoid curbs when negotiating sidewalks in urban environment. The advantage of using PTI over the conventional traversability index is that the robot’s yaw angle is taken into account when computing the terrain traversal property at the corresponding direction. This allows the robot to snake up a steep ramp that may be too steep for the robot to climb if the conventional traversibility index were used. The efficacies of the PTI and the entire system have been verified by simulation and experiments with a real robot.