Risk-Aware Decentralized Multi-MAV Planning in Unknown and Dynamic Environments

Recent progress in multiple micro aerial vehicle (MAV) systems has demonstrated autonomous navigation in static environments. Yet, there are limited works regarding the autonomous navigation of multiple MAVs in dynamic and unknown environments. The challenge arises from the complexity of the motion planning problem, which requires the MAVs to...

Indoor swarm exploration with Pocket Drones

Pocket drones, weighing less than 50 grams, are small, agile and inherently safe. This makes them suitable for several surveillance tasks such as search and rescue, green-house monitoring and pipe-line inspection. In order for a more efficient search, a swarm of pocket drones would be ideal to explore these types of areas faster. Current methods...

Real-time Vision-based Autonomous Navigation of MAV in Dynamic Environments

Safe navigation in unknown environments is a challenging task for autonomous Micro Aerial Vehicle (MAV) systems. Previous works generally avoid obstacles by assuming that the environment is static. The purpose of this thesis work is to develop a MAV system that can navigate autonomously and safely in dynamic environments. We present an onboard...

Online Trajectory Planning and Control of a MAV Payload System in Dynamic Environments: A Non-Linear Model Predictive Control Approach

Micro Aerial Vehicles (MAVs) are increasingly being used for aerial transportation in remote and urban spaces where portability can be exploited to reach previously inaccessible and inhospitable spaces. Current approaches to MAV swung payload system path planning have primarily focused on pre-generating (agile) collision-free, or conservative...