Estimation of Time-to-Contact for Navigation of Autonomous Robots Using Parallel Processing

Given the trend of more complex tasks that robots should perform, we need to design increasingly robust solutions to perform tasks more efficiently and above all, real-time calculations. One of the most important tasks of a mobile robot is navigating through a room avoiding obstacles with which it may collide. Our contribution is to show how to compute efficiently time-to-contact for avoiding collisions in robotic navigation, using Graphics Processor Unit (GPU) and Compute Unified Device Architecture (CUDA). Description of the problem in different size of images and the complexity analysis of sequential and parallel ways are described. Finally, experimental results with synthetic and real images are shown.