Multi-robot Task Assignment for Aerial Tracking with Viewpoint Constraints

We address the problem of assigning a team of drones to autonomously capture a set desired shots of a dynamic target in the presence of obstacles. We present a two-stage planning pipeline that generates offline an assignment of drone to shots and locally optimizes online the viewpoint. Given desired shot parameters, the high-level planner uses a visibility heuristic to predict good times for capturing each shot and uses an Integer Linear Program to compute drone assignments. An online Model Predictive Control algorithm uses the assignments as reference to capture the shots. The algorithm is validated in hardware with a pair of drones and a remote controlled car.

Authors

• Aaron Ray
• Alyssa Pierson
• Hai Zhu 0002
• Javier Alonso-Mora
• Daniela Rus

Keywords

• Uncertainty
• Target tracking
• Pipelines
• Prediction algorithms
• Trajectory
• Planning
• Task analysis
• Local Optimum
• Model Predictive Control
• Presence Of Obstacles
• Model Predictive Control Algorithm
• High-level Planner
• Predictive Control Algorithm
• Field Of View
• Time Step
• Cost Function
• Nonlinear Programming
• Constrained Optimization Problem
• Reference Position
• Partial Order
• Reference Trajectory
• Assignment Problem
• Planning Algorithm
• Unique Color
• Target Trajectory
• Reference Path
• Target Frame
• Shot Sequence
• Target View
• Ray Casting
• Race Car
• Minimum Cost Flow
• Time Ta
• Directed Acyclic Graph
• Visual Target