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...

Direct sensor integration for optimization fabrics

Autonomous robots hold great potential for positive impacts on society by applying them to tasks that are hazardous, repetitive, or complex and difficult for humans to perform. To achieve these tasks, autonomous robots require the ability to perceive environmental changes and create corresponding motion plans, which involve a combination of...

Trajectory Optimization for Autonomous Navigation in Dynamic Environments

Motion planning for Autonomous Ground Vehicles (AGVs) in dynamic environments is an extensively studied and complex problem. State of the art methods provide approximate solutions that make conservative assumptions to provide safety and feasibility. We aim to outperform current methods by following a trajectory optimization-based approach,...