Multi-robot Task Allocation using Agglomerative Clustering

The main objective of this thesis is to solve the problem of balancing tasks in the Multi-robot Task Allocation problem domain. When allocating a large number of tasks to a multi-robot system, it is important to balance the load effectively across the robots in the system. In this thesis an algorithm is proposed in which tasks are allocated through clustering, investigating the effectiveness of agglomerative hierarchical clustering as compared to K-means clustering. Once the tasks are clustered, each agent claims a cluster through a greedy self-assignment. This thesis investigates the performance both when all tasks are known ahead of time as well as when new tasks are injected into the system periodically. To account for new tasks, both global re-clustering and greedy clustering methods are considered. Three metrics: 1) total travel cost, 2) maximum distance traveled per robot, and 3) balancing cost index are used to compare the performance of the overall system in environments both with and without obstacles. The results collected from the experiments show that agglomerative hierarchical clustering is deterministic and better at minimizing the total travel cost, especially for large numbers of agents, whereas K-means works better to balance costs. In addition to this, the greedy approach for clustering new tasks works better for frequently appearing tasks than infrequent ones

A New Method for Improving the Fairness of Multi-Robot Task Allocation by Balancing the Distribution of Tasks

This paper presents an innovative task allocation method for multi-robot systems that aims to optimize task distribution while taking into account various performance metrics such as efficiency, speed, and cost. Contrary to conventional approaches, the proposed method takes a comprehensive approach to initialization by integrating the K-means clustering algorithm, the Hungarian method for solving the assignment problem, and a genetic algorithm specifically adapted for Open Loop Travel Sales Man Problem (OLTSP). This synergistic combination allows for a more robust initialization, effectively grouping similar tasks and robots, and laying a strong foundation for the subsequent optimization process. The suggested method is flexible enough to handle a variety of situations, including Multi-Robot System (MRS) with robots that have unique capabilities and tasks of varying difficulty. The method provides a more adaptable and flexible solution than traditional algorithms, which might not be able to adequately address these variations because of the heterogeneity of the robots and the complexity of the tasks. Additionally, ensuring optimal task allocation is a key component of the suggested method. The method efficiently determines the best task assignments for robots through the use of a systematic optimization approach, thereby reducing the overall cost and time needed to complete all tasks. This contrasts with some existing methods that might not ensure optimality or might have limitations in their ability to handle a variety of scenarios. Extensive simulation experiments and numerical evaluations are carried out to validate the method's efficiency. The extensive validation process verifies the suggested approach's dependability and efficiency, giving confidence in its practical applicability

Development of personal area network (PAN) for mobile robot using bluetooth transceiver

The work presents the concept of providing a Personal Area Network (PAN) for microcontroller based mobile robots using Bluetooth transceiver. With the concept of replacing cable, low cost, low power consumption and communication range between 10m to 100m, Bluetooth is suitable for communication between mobile robots since most mobile robots are powered by batteries and have high mobility. The network aimed to support real-time control of up to two mobile robots from a master mobile robot through communication using Bluetooth transceiver. If a fast network radio link is implemented, a whole new world of possibilities is opened in the research of robotics control and Artificial Intelligence (AI) research works, sending real time image and information. Robots could communicate through obstacles or even through walls. Bluetooth Ad Hoc topology provides a simple communication between devices in close by forming PAN. A system contained of both hardware and software is designed to enable the robots to form a PAN and communicating, sharing information. Three microcontroller based mobile robots are built for this research work. Bluetooth Protocol Stack and mobile robot control architecture is implemented on a single microcontroller chip. The PAN enabled a few mobile robots to communicate with each other to complete a given task. The wireless communication between mobile robots is reliable based from the result of experiments carried out. Thus this is a platform for multi mobile robots system and Ad Hoc networking system. Results from experiments show that microcontroller based mobile robots can easily form a Bluetooth PAN and communicate with each other