DTA-HMR-TT: Dynamic Task Allocation for a Heterogeneous Team of Mobile Robots With Task Transfer

Managing time-sensitive deliveries in settings like hospitals is a challenging task, especially when multiple pickup and delivery requests need to be coordinated efficiently within strict time windows. This paper focuses on the Multi-Pickup and Delivery Problem with Time Windows (MPDPTW), where a fleet of autonomous mobile robots works together to fulfill client requests that involve picking up items from specified origins and delivering them to designated destinations. Our objective is to minimize penalties associated with late deliveries while maximizing the number of successfully completed requests. To address this, we introduce a novel approach using a heterogeneous team of robots equipped with an efficient and cost-effective scheduling algorithm. Users submit requests with specific time constraints, and our proposed decentralized algorithm-Dynamic Task Allocation for Heterogeneous Mobile Robots with Task Transfer (DTA-HMR-TT)-optimizes task sharing between robots, ensuring timely service. The algorithm dynamically adjusts to handle rejected or delayed tasks and manages the complex transfer of tasks between robots to improve delivery efficiency. Extensive simulations have demonstrated that our approach significantly outperforms state-of-the-art methods. For smaller task sets (50 to 150 tasks), penalties were reduced by 27%, while for larger sets (150 to 300 tasks), penalties were lowered by 36%. Our results highlight the effectiveness of DTA-HMR-TT in enhancing task scheduling and coordination in multi-robot systems, offering a promising solution for improving delivery performance in structured environments.