Enhancing the Reactivity of the Vision Subsystem in Autonomous Mobile Robots Using Real-Time Techniques
Interest on using mobile autonomous agents has been growing, recently, due to their capacity to cooperate for diverse purposes, from rescue to demining and security. In many of these applications the environments are inherently unstructured and dynamic, requiring substantial computation resources for gathering enough sensory input data to allow a safe navigation and interaction with the environment. As with humans, who depend heavily on vision for these purposes, mobile robots employ vision frequently as the primary source of input data when operating in such environments. However, vision-based algorithms are seldom developed with reactive and real-time concerns, exhibiting large variations in the execution time and leading to occasional periods of black-out or vacant input data. This paper addresses this problem in the scope of the CAMBADA robotic soccer team developed at the University of Aveiro, Portugal. It presents an evolution from a monolithic to a modular architecture for the vision system that improves its reactivity. With the proposed architecture it is possible to track different objects with different rates without losing any frames.
KeywordsController Area Network Modular Architecture Obstacle Detection Autonomous Mobile Robot Robotic Agent
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