Development of task distribution algorithm for multi-robot coordination system

• Main Author: Sin, Han Bin
• Format: Final Year Project / Dissertation / Thesis
• Published: 2022
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utar.edu.my/5391/1/MH_1704516_Final_%2D_HAN_BIN_SIN.pdf; http://eprints.utar.edu.my/5391/

Multi-Robot system consists of a group of autonomous robots that work together to accomplish the given tasks to achieve a specific goal. In the era of advanced technology, a single robot is replaced by multiple robots with different capabilities in the industry due to their fault-tolerance and efficiency in terms of cost and time for task execution. Delivery is the most common task implemented by a MultiRobot system in a manufacturing industry. However, task allocation to a group of heterogeneous robots is challenging as allocation of the same task to multiple robots is commonly occurred. The problem always arises when robots are navigating such as the collision between robots and obstacles. Hence, an effective task distribution algorithm is important to allocate tasks correctly among the robots with optimum cost and time utilization. Besides, proper navigation techniques allow robots to avoid collisions and obstacles during task execution. Software such as Robot Operating System 2 (ROS2), Gazebo, ROS Visualization 2 (RViz2), and Robotics Middleware Framework (RMF) are utilized for the development and simulation of the project. During the development process, the simulation environment is modeled with desired task points, robots, and traffic lanes. Algorithms are integrated with RMF for task distribution and path planning for the robots. Whereas robots’ motion at the designated path is visualized through RViz2. The project simulation is carried out in Gazebo to validate the performance of the algorithms. RMF Panel provides an online platform to perform task submission and enables real-time visualization of task distribution of robots as well as robots’ status. Effective task distribution and self-navigation of robots are simulated in Gazebo and RViz2 respectively with the integration of the RMF framework and ROS2. The delivery tasks are distributed efficiently among the respective robots which have obstacle avoidance and traffic conflict resolved capabilities in the simulation.