Perception-driven multi-robot formation control

Maximizing the performance of cooperative perception of a tracked target by a team of mobile robots while maintaining the team's formation is the core problem addressed in this work. We propose a solution by integrating the controller and the estimator modules in a formation control loop. The controller module is a distributed non-linear model predictive controller and the estimator module is based on a particle filter for cooperative target tracking. A formal description of the integration followed by simulation and real robot results on two different teams of homogeneous robots are presented. The results highlight how our method successfully enables a team of homogeneous robots to minimize the total uncertainty of the tracked target's cooperative estimate while complying with the performance criteria such as keeping a pre-set distance between the team-mates and/or the target and obstacle avoidance.

Authors

• Aamir Ahmad
• Tiago Pereira do Nascimento
• André Gustavo Scolari Conceição
• António Paulo Moreira
• Pedro U. Lima

Keywords

• Target tracking
• Robot sensing systems
• Cost function
• Robot kinematics
• Collision avoidance
• Uncertainty
• Formation Control
• Multi-robot Formation Control
• Control Mode
• Model Predictive Control
• Particle Filter
• Nonlinear Control
• Obstacle Avoidance
• Real Robot
• Swarm Robotics
• Estimation Module
• Nonlinear Model Predictive Control
• Collision
• Simulation Experiments
• Target Location
• Control Signal
• Proportionality Constant
• Ground Plane
• Prediction Horizon
• Pre-defined Model
• Target Velocity
• Fisheye Lens
• Mobile Sensors
• Global Frame
• Coordination Variability
• Static Obstacles
• Distributed Architecture
• Communication Failure
• Target Frame