# Search-based 3D Planning and Trajectory Optimization for Safe Micro Aerial Vehicle Flight Under Sensor Visibility Constraints

## TL;DR

This paper introduces a search-based planning and trajectory optimization method for MAVs that accounts for sensor visibility constraints, dynamic obstacles, and flight dynamics to ensure safe navigation.

## Contribution

It presents a novel combined planning and optimization approach that considers sensor coverage limitations and flight dynamics for safe MAV navigation.

## Key findings

- Successful implementation on DJI Matrice 600 MAV
- Effective obstacle avoidance with sensor visibility constraints
- Validated through hardware-in-the-loop simulation

## Abstract

Safe navigation of Micro Aerial Vehicles (MAVs) requires not only obstacle-free flight paths according to a static environment map, but also the perception of and reaction to previously unknown and dynamic objects. This implies that the onboard sensors cover the current flight direction. Due to the limited payload of MAVs, full sensor coverage of the environment has to be traded off with flight time. Thus, often only a part of the environment is covered. We present a combined allocentric complete planning and trajectory optimization approach taking these sensor visibility constraints into account. The optimized trajectories yield flight paths within the apex angle of a Velodyne Puck Lite 3D laser scanner enabling low-level collision avoidance to perceive obstacles in the flight direction. Furthermore, the optimized trajectories take the flight dynamics into account and contain the velocities and accelerations along the path. We evaluate our approach with a DJI Matrice 600 MAV and in simulation employing hardware-in-the-loop.