MRI: Acquisition of mobile robots to support indoor navigation and online 3D object detection

Cuny Hunter College, New York NY

Investigators

Abstract

Mobile intelligent robots are used today in the domain of assisted living and health care, as they can accompany people, assist them, and be used to effectively support various applications, such as navigation. This project called SemaFORR, uses two robots equipped with multiple real-world sensors to provide cognitively plausible solution when traditional navigation assumptions cannot be used. The robots are equipped to provide an autonomous navigation and real time classification from 3D range data. The project highlights the role of cognition in navigation, enhancing the image-understanding capabilities of mobile robots by pushing the state of the art in classification algorithms. Addressing fundamental issues in multi-method search, inference learning, representation, online quickest detection and classification that contribute in solving challenging problems, the project involves increasing the image-understanding capabilities of mobile robots. This goal is to be accomplished by developing real time classification and object detection to help computers and people solve challenging problems. Operating under the open-source standard ROS (Robot Operating System) serves as the base on which to build and test algorithms to: 1. Enhance navigation with cognitive plausible decision making by integrating a novel architectural method that enables the robot to learn a dynamic spatial model that diagrams special affordances; 2. Enhance online real-time object detection and classification by performing a stage-based 3D classification; and 3. Optimize algorithms by balancing the tradeoff between accuracy and speed of object classification.