Optimal Trajectory Planning for Cinematography with Multiple Unmanned Aerial Vehicles

Abstract

This paper presents a method for planning optimal trajectories with a team of Unmanned Aerial Vehicles (UAVs) performing autonomous cinematography. The method is able to plan trajectories online and in a distributed manner, providing coordination between the UAVs. We propose a novel non-linear formulation for this challenging problem of computing multi-UAV optimal trajectories for cinematography; integrating UAVs dynamics and collision avoidance constraints, together with cinematographic aspects like smoothness, gimbal mechanical limits and mutual camera visibility. We integrate our method within a hardware and software architecture for UAV cinematography that was previously developed within the framework of the MultiDrone project; and demonstrate its use with different types of shots filming a moving target outdoors. We provide extensive experimental results both in simulation and field experiments. We analyze the performance of the method and prove that it is able to compute online smooth trajectories, reducing jerky movements and complying with cinematography constraints.

arXiv commentThis paper has been published as: Optimal trajectory planning for cinematography with multiple Unmanned Aerial Vehicles. Alfonso Alcantara and Jesus Capitan and Rita Cunha and Anibal Ollero. Robotics and Autonomous Systems. 103778 (2021) 10.1016/j.robot.2021.103778

References in corpus (6)

• Airways: Optimization-Based Planning of Quadrotor Trajectories according to High-Level User Goals
• Deep Neural Network-based Cooperative Visual Tracking through Multiple Micro Aerial Vehicles
• Towards a Drone Cinematographer: Guiding Quadrotor Cameras using Visual Composition Principles
• Decentralized MPC based Obstacle Avoidance for Multi-Robot Target Tracking Scenarios
• Autonomous Execution of Cinematographic Shots with Multiple Drones
• Autonomous Reflectance Transformation Imaging by a Team of Unmanned Aerial Vehicles

Cited by in corpus (6)

• Autonomous Aerial Filming With Distributed Lighting by a Team of Unmanned Aerial Vehicles
• Autonomous Execution of Cinematographic Shots with Multiple Drones
• Flying in Highly Dynamic Environments with End-to-end Learning Approach
• A Signal Temporal Logic Motion Planner for Bird Diverter Installation Tasks with Multi-Robot Aerial Systems
• Aerial Field Robotics
• Polar Coordinate-based Differential Evolution for Moving Target Search Using Vision Sensor on Unmanned Aerial Vehicles