Quadrotors are unique among Micro Aerial Vehicles in providing excellent maneuverability (as opposed to winged flight),while maintaing a simple mechanical construction (as opposed to helicopters). This mechanical simplicity comes at a cost of increased controller complexity. Quadrotors are inherently unstable, in the sense that they are essentially unflyable by a...
This thesis addresses Micro Aerial Vehicle (MAV) control by leveraging learning based techniques to improve robustness of the control system. Applying classical control methods to MAVs is a difficult process due to the complexity of the control laws with fast and highly non-linear dynamics. These methods are mostly based on...
The use of autonomous robots in complex exploration tasks is rapidly increasing. Indeed, robots can provide speed and cost effectiveness in many tasks, as well as allow operation in environments that are hostile to humans. In this dissertation we: 1) provide two adaptive navigation algorithms; 2) develop a coordination mechanism;...
This thesis explores the implementation of learning based control with predictive cruise control and the potential this technology has for increasing fuel efficiency while keeping on a well maintained schedule for commercial trucks. Traditional cruise control is wasteful when maintaining a constant velocity over rolling hills. Predictive cruise control is...
Coordination in large multiagent systems in order to achieve a system level goal is a critical challenge. Given the agents' intention to cooperate, there is no guarantee that the agent actions will lead to good system objective especially when the system becomes large. One of the primary difficulties in such...