# Online Trajectory Generation of a MAV for Chasing a Moving Target in 3D Dense Environments

## TL;DR

This paper presents a real-time trajectory generation method for a MAV to chase a moving target in dense 3D environments, handling collision avoidance, occlusion, and visibility optimization through a cascaded planning approach.

## Contribution

It introduces a novel cascaded planner combining graph-search and quadratic programming for safe, efficient, and visibility-aware target chasing in cluttered environments.

## Key findings

- Successfully tested in dense environments with real-time replanning
- Ensures collision avoidance and target visibility
- Provides a complete simulation tool with code and GUI

## Abstract

This work deals with a moving target chasing mission of an aerial vehicle equipped with a vision sensor in a cluttered environment. In contrast to obstacle-free or sparse environments, the chaser should be able to handle collision and occlusion simultaneously with flight efficiency. In order to tackle these challenges with real-time replanning, we introduce a metric for target visibility and propose a cascaded chasing planner. By means of the graph-search methods, we first generate a sequence of chasing corridors and waypoints which ensure safety and optimize visibility. In the following phase, the corridors and waypoints are utilized as constraints and objective in quadratic programming from which we complete a dynamically feasible trajectory for chasing. The proposed algorithm is tested in multiple dense environments. The simulator AutoChaser with full code implementation and GUI can be found in https://github.com/icsl-Jeon/traj_gen_vis