Since 2007 and started from an NSERC Strategic Project Grant entitled “Cooperative UAV Systems with Increased Reliability in Severe Environments,” Concordia University has started a long-term and closed collaboration with Quanser on making use of Quanser’s cutting-edge unmanned systems on air (UAVs: QBall, QDrone) and ground (UGVs: QBot, QCar) for developing advanced Autonomous Control (AC), Fault-Tolerant Control (FTC), and Fault-Tolerant Cooperative Control (FTCC) techniques. Such platforms have been used for undergraduate and graduate course “Flight Control Systems” teaching since Fall 2010 and research work for applications to forest fires monitoring and detection, autonomous vehicles etc. for investigating concepts and carrying out research on Fault Detection and Diagnosis (FDD), FTC, and FTCC techniques.
This webinar covers two main topics. First will be a brief overall view of the challenges and latest developments on making unmanned systems smarter, safer, and more reliable & resilient in terms of Guidance, Navigation, and Control (GNC) of unmanned systems with the integration of Remote Sensing (RS) techniques for autonomous, efficient, reliable and secure applications to forest and environment monitoring and fires/damages/risks detection. The second part of the presentation will introduce some of the new developments and current research. In particular, new developments on AC, FDD, FTC, and FTCC techniques for autonomous and reliable applications to the forest fire monitoring tasks based on using QBall, QDrone, and QCar will be presented. New developments will also be presented for efficient and reliable detection of fires/damages/risks based on remotely sensed signals/images from onboard UAVs.
QCar, the feature vehicle of the Self-Driving Car Research Studio, is an open-architecture, scaled model vehicle designed for academic research. Working individually or in a fleet, QCar is the ideal vehicle for validating dataset generation, mapping, navigation, machine learning, artificial intelligence, and other advanced self-driving concepts.
The Quanser QBot 3 is an innovative open-architecture autonomous ground robot, built on a 2-wheel mobile platform. Equipped with built-in sensors, a vision system, and accompanied by extensive courseware, the QBot 3 is ideally suited for teaching undergraduate and advanced robotics and mechatronics courses.
