A Generalized Framework for Solving Tightly-coupled Multirobot Planning Problems

In this paper, we present the generalized version of the Hoplites coordination framework designed to efficiently solve complex, tightly-coupled multirobot planning problems. Our extensions greatly increase the flexibility with which teammates can both plan and coordinate with each other; consequently, we can apply Hoplites to a wider range of domains and plan coordination between robots more efficiently. We apply our framework to the constrained exploration domain and compare Hoplites in simulation to competing distributed and centralized approaches. Our results demonstrate that Hoplites significantly outperforms both approaches in terms of the quality of solutions produced while remaining computationally competitive with much simpler approaches. We further demonstrate features such as scalability and validate our approach with field results from a team of large autonomous vehicles performing constrained exploration in an outdoor environment

Authors

• Nidhi Kalra
• Dave Ferguson 0001
• Anthony Stentz

Keywords

• Robot kinematics
• Orbital robotics
• Robotics and automation
• Computational modeling
• Remotely operated vehicles
• Mobile robots
• Scalability
• Collaborative work
• Safety
• Relays
• Autonomous Vehicles
• Centralized Approach
• Coordination Framework
• Planning Coordination
• Line-of-sight
• Efficient Solution
• Simultaneous Activation
• Problem Instances
• Cost-effective Solution
• Planning Time
• Relaxed Constraints
• Constraint Violation
• Planning Algorithm
• Central Planning
• Team Size
• Traveling Salesman Problem
• Swarm Robotics
• Team Structure
• Difficult Scenarios
• Sampling-based Methods
• Tight Coordination
• Reservation Price
• Team Resources
• Flexible Coordination
• Laser Ranging
• Relay Nodes