A Vision-Based Road Surface Slope Estimation Algorithm for Mobile Service Robots in Indoor Environments

It is vital for mobile robots to maintain safe and stable operation in environments with slopes, e.g. airports and shopping malls. Different slopes correspond to different accelerations of robots, and the robot also require different driving forces or braking forces to go up or down different slopes. If the robot does not have the ability to recognize of the slope, it cannot generate suitable commands according to the change of slope. That is to say, when going uphill, the lack of driving force may cause the robot to stagnate on the slope; when downhill, insufficient braking force may cause the robot to lose control. To solve such problems, a slope estimation algorithm is proposed in this paper based on RGB-D camera. Firstly, we use the RGB-D camera to obtain the information of the road surface. Secondly, the edge of the slope is detected by Canny Edge Detection Algorithm. Finally, the slope is estimated based on the mathematical geometry. Experimental studies are carried out to evaluate the proposed slope estimation algorithm. Experimental results show that the slope of the road can be obtained in real time and the average slope estimation error is less than 5°.