Autonomous Aerial Filming With Distributed Lighting by a Team of Unmanned Aerial Vehicles

Abstract

This paper describes a method for autonomous aerial cinematography with distributed lighting by a team of unmanned aerial vehicles (UAVs). Although camera-carrying multirotor helicopters have become commonplace in cinematography, their usage is limited to scenarios with sufficient natural light or of lighting provided by static artificial lights. We propose to use a formation of unmanned aerial vehicles as a tool for filming a target under illumination from various directions, which is one of the fundamental techniques of traditional cinematography. We decompose the multi-UAV trajectory optimization problem to tackle non-linear cinematographic aspects and obstacle avoidance at separate stages, which allows us to re-plan in real time and react to changes in dynamic environments. The performance of our method has been evaluated in realistic simulation scenarios and field experiments, where we show how it increases the quality of the shots and that it is capable of planning safe trajectories even in cluttered environments.

Mission Planning and Execution in Heterogeneous Teams of Aerial Robots supporting Power Line Inspection Operations

“…In the inspection operations, the low-level controller encodes the mission execution as a trajectory planning problem where the vehicles need to move from an initial position and through a sequence of target points, while avoiding obstacles and maintaining a safety distance between them [14]. In the monitoring operations,the corresponding low-level controller solves a formation control problem where the vehicles need to keep the human worker within the camera frame during the entire operation, providing complementary views from multiple angles [23], [24]. In both tasks, quadrotor UAVs support maintenance operations.…”

“…After mission planning, the High-Level Planner outputs a list of assigned and feasible tasks for each UAV. The tasks are provided as inputs to the N-instances of the Agent Behavior Manager, as many as the available vehicles, which are in charge of extracting the tasks' parameters for the corresponding Low-Level Controllers where complex behaviors are encoded [14], [23]- [25].…”

An Application of Stereo Thermal Vision for Preliminary Inspection of Electrical Power Lines by MAVs

“…However, the use of UAVs to achieve these tasks is particularly challenging, due to their limited battery capacity, the strong electromagnetic interference produced by power towers, and the presence of potential obstacles along the lines (e.g., branches, vegetation, marker balls) [9]. Small and lightweight systems with cognitive capabilities, e.g., based on novel perception sensors [10], advanced data fusion techniques [11], planning [12], [13] and control algorithms [14], are of interest to address those complexities and to accomplish the assigned mission safely and successfully. More precisely, it is key to integrate small UAVs (see Fig.…”

A Perception-Aware NMPC for Vision-Based Target Tracking and Collision Avoidance with a Multi-Rotor UAV

“…In the last decade, the research and commercial interest on Unmanned Aerial Vehicles (UAVs) has exploded as demonstrated by the growing number of applications, such as infrastructure monitoring [1], aerial filming [2], surveillance and search and rescue missions [3] and wireless communications [4]. Most of these applications require UAVs with visual sensors and with certain autonomy that enable them to rapidly react in dynamic environments to successfully accomplish their mission.…”