Event Driven CBBA with Reduced Communication
By: Vinita Sao , Tu Dac Ho , Sujoy Bhore and more
Potential Business Impact:
Robots share jobs better with less talking.
In various scenarios such as multi-drone surveillance and search-and-rescue operations, deploying multiple robots is essential to accomplish multiple tasks at once. Due to the limited communication range of these vehicles, a decentralised task allocation algorithm is crucial for effective task distribution among robots. The consensus-based bundle algorithm (CBBA) has been promising for multi-robot operation, offering theoretical guarantees. However, CBBA demands continuous communication, leading to potential congestion and packet loss that can hinder performance. In this study, we introduce an event-driven communication mechanism designed to address these communication challenges while maintaining the convergence and performance bounds of CBBA. We demonstrate theoretically that the solution quality matches that of CBBA and validate the approach with Monte-Carlo simulations across varying targets, agents, and bundles. Results indicate that the proposed algorithm (ED-CBBA) can reduce message transmissions by up to 52%.
Similar Papers
Bayesian Decentralized Decision-making for Multi-Robot Systems: Sample-efficient Estimation of Event Rates
Robotics
Robots find safest place by learning from each other.
Multi Robot Coordination in Highly Dynamic Environments: Tackling Asymmetric Obstacles and Limited Communication
Robotics
Robots share tasks better with bad radios.
A Group Consensus-Driven Auction Algorithm for Cooperative Task Allocation Among Heterogeneous Multi-Agents
Multiagent Systems
Helps robots finish jobs faster and more accurately.