Onboard Visual Control of a Quadcopter MAV performing a Landing Task: on a Platform of Unknown Size and Location

Vision based control allows Micro Air Vehicles (MAV) to move autonomously in GPS-denied environments, for example in indoor applications. An open issue in this field is landing on an unknown platform. The difficulty in visual control w.r.t. such an unknown platform, is a lack of scale. Without knowledge of the scale of offsets and object sizes ...

Neuromorphic Computing of Event-Based Data for High-Speed Vision-Based Navigation

The combination of Spiking Neural Networks and event-based vision sensors holds the potential of highly efficient and high-bandwidth optical flow estimation. This thesis presents, to the best of the author’s knowledge, the first hierarchical spiking architecture in which motion (direction and speed) selectivity emerges in a biologically...

Directed Increment Policy Search for Behavior Tree Task Performance Optimization: Crossing the Reality Gap

Robotic behavior policies learned in simulation suffer from a performance degradation once transferred to a real-world robotic platform. This performance degradation originates from discrepancies between the real-world and simulation environment, referred to as the reality gap. To cross the reality gap, this papers presents a simple...

Reinforcement Learning Policy Approximation by Behavior Trees: using Genetic Algoritms

Autonomous Collision Avoidance for Swarms of MAVs: Based solely on RSSI measurements

Swarming is a promising solution for extending the flight time and payload carrying capabilities of Micro Aerial Vehicles (MAVs), where recent years have brought many advancements. These allow MAVs to operate ever more autonomously by tackling problems such as obstacle avoidance and autonomous navigation. A major challenge that still remains,...