Multi Robot Cooperative System For Object Detection

Multi Robot Cooperative System for Object Detection

Multi-Robot Task Allocation for Inspection Problems with Cooperative Tasks Using Hybrid Genetic Algorithms

In this dissertation, methods for optimal multi-robot task allocation (MRTA) for industrial plant inspection are investigated. MRTA involves distributing and scheduling a set of tasks for a group of robots to minimize the total cost taking into account operational constraints. With technical progress and declining cost of robotic mobility, interest in industrial mobile robotics has grown significantly in recent years. Many efforts have been devoted to mobility-related problems such as self-localization and mapping, though only few studies deal with the optimal task allocation in multi-robot systems. Since a good task allocation provides more efficient scheduling (e.g. less cost, shorter time), the objective of this research is to develop search/optimization methods for inspection problems that involve both single- and two-robot tasks.

Distributed Optimisation for Multi-Robot Cooperative Manipulation Control in Dynamic Environments

Since the manipulation tasks for robotic systems become more and more complicated, multi-robot cooperation has been attracting much attention recently. Furthermore, under the trend of human-robot co-existence, collision-free motion control is now also desired on multi-robot groups. This dissertation aims to design a novel distributed optimal control framework to deal with multi-robot cooperative manipulation of rigid objects in dynamic environments. Besides object transportation, the control scheme also tackles obstacle avoidance, joint-space performance optimisation and internal force suppression. The proposed control framework has a two-layer structure, with a distributed optimisation algorithm in the kinematic layer for generating proper joint configuration references, followed by a robot motion controller in the dynamic control layer to fulfil the reference. An indirect and a direct distributed optimisation method are developed for the kinematic layer, both of which are computationally and communicationally efficient. In the dynamic control layer, impedance control is employed for safe physical interaction. As another highlight, abundant experiments carried out on a multi-arm test bench have demonstrated the effectiveness of the presented control schemes under various environmental and task settings. The recorded computation time shows the applicability of the control framework in practice.