Autonomous Multi-robot System Research Articles

A multirobot system for autonomous deployment and recovery of a blade crawler for operations and maintenance of offshore wind turbine blades

AbstractOffshore wind farms will play a vital role in the global ambition of net zero energy generation. Future offshore wind farms will be larger and further from the coast, meaning that traditional human‐based operations and maintenance approaches will become infeasible due to safety, cost, and skills shortages. The use of remotely operated or autonomous robotic assistants to undertake these activities provides an attractive alternative solution. This paper presents an autonomous multirobot system which is able to transport, deploy and retrieve a wind turbine blade inspection robot using an unmanned aerial vehicle (UAV). The proposed solution is a fully autonomous system including a robot deployment interface for deployment, a mechatronic link‐hook module (LHM) for retrieval, both installed on the underside of a UAV, a mechatronic on‐load attaching module installed on the robotic payload and an intelligent global mission planner. The LHM is integrated with a 2‐DOF hinge that can operate either passively or actively to reduce the swing motion of a slung load by approximately 30%. The mechatronic modules can be coupled and decoupled by special maneuvers of the UAV, and the intelligent global mission planner coordinates the operations of the UAV and the mechatronic modules for synchronous and seamless actions. For navigation in the vicinity of wind turbine blades, a visual‐based localization merged with the location knowledge from Global Navigation Satellite System has been developed. A proof‐of‐concept system was field tested on a full‐size decommissioned wind‐turbine blade. The results show that the experimental system is able to deploy and retrieve a robotic payload onto and from a wind turbine blade safely and robustly without the need for human intervention. The vicinity localization and navigation system have shown an accuracy of 0.65 and 0.44 m in the horizontal and vertical directions, respectively. Furthermore, this study shows the feasibility of systems toward autonomous inspection and maintenance of offshore windfarms.

A virtual force interaction scheme for multi-robot environment monitoring

The autonomous multi-robot system is an emerging technology that has a wide range of potential applications, such as environmental monitoring, exploration of unknown area, battlefield surveillance, and search and rescue. One major challenge in such applications is how to deploy each robotic agent autonomously in a distributed manner. In this paper, we proposed a distributed coverage control strategy named multi-stage virtual force interaction scheme (VFIS), where the agents’ deployment process is split into stages and each agent iteratively seeks its next position according to the interaction among agents and the interaction between agents and the perceived environment. The interactions are realized via virtual repulsive forces and virtual vortex forces, where the latter are newly proposed to enhance the exploration capability of agents. We also designed a group of benchmark testing problems for the mission of monitoring coverage of complex environments with unknown obstacles. Extensive simulation experiments were conducted based on the defined benchmark configurations and the results showed a favorable performance of the invented strategy. In addition, practical experiments were carried out using a group of mobile robots, which validated the effectiveness of the proposed method.

Task allocation and coordinated motion planning for autonomous multi-robot optical inspection systems

Autonomous multi-robot optical inspection systems are increasingly applied for obtaining inline measurements in process monitoring and quality control. Numerous methods for path planning and robotic coordination have been developed for static and dynamic environments and applied to different fields. However, these approaches may not work for the autonomous multi-robot optical inspection system due to fast computation requirements of inline optimization, unique characteristics on robotic end-effector orientations, and complex large-scale free-form product surfaces. This paper proposes a novel task allocation methodology for coordinated motion planning of multi-robot inspection. Specifically, (1) a local robust inspection task allocation is proposed to achieve efficient and well-balanced measurement assignment among robots; (2) collision-free path planning and coordinated motion planning are developed via dynamic searching in robotic coordinate space and perturbation of probe poses or local paths in the conflicting robots. A case study shows that the proposed approach can mitigate the risk of collisions between robots and environments, resolve conflicts among robots, and reduce the inspection cycle time significantly and consistently.

An improved DPoS consensus mechanism in blockchain based on PLTS for the smart autonomous multi-robot system

Due to the development of robot technology, smart autonomous multi-robot systems face different security problems such as data loss and vulnerabilities. However, the robot information stored in blockchain can be more transparent and effective at ensuring the security of the robot system due to the decentralization, tamper-proof and anonymity of blockchain. In the architectural composition of blockchain, Delegated Proof of Stake (DPoS) consensus mechanism is playing a critical role with more decentralization, lower energy consumption and faster confirmation speed. Similar to the board voting, the holders cast a certain number of delegates to perform verification and block generating on their behalf in DPoS. In order to improve the efficiency and flexibility of DPoS consensus mechanism, we propose an improved DPoS consensus mechanism based on the Probabilistic Linguistic Term Set (PLTS) for the smart autonomous multi-robot system. By adding voting options for nodes, the Voting Algorithm with Probabilistic Linguistic Information (VAPLI) calculates the score and deviation degree of each node after tabulating the voting results. The selection of a delegate is based on the comparison of the score and deviation degree. Finally, we explore the model implementation of the improved DPoS consensus mechanism, and verify its feasibility and effectiveness using examples.

Study on the Autonomous Multirobot Collaborative Control System Based on Spherical Amphibious Robots

The study on the multirobot collaborative control method has broad application prospect and value in the field of robotics. To adapt to a variety of working environments and higher efficiency, this article designed the autonomous multirobot collaborative control system based on spherical amphibious robots. First, this article proposed the formation strategy for spherical amphibious multirobot and used linear quadratic regulator algorithm to adjust the robot trajectory. Then, this article used XBee wireless communication with excellent communication performance under low noise ratio conditions to complete real-time information sharing of multirobot. Finally, based on the theoretical analysis and calculation, a series of land and underwater evaluation experiments were carried out to verify the feasibility of autonomous multirobot collaborative control system. The experimental results showed that the spherical amphibious multirobot could realize collaborative control accurately under different environments according to the predetermined trajectory.

Autonomous multi-robot tracking system for oil spills on sea surface based on hybrid fuzzy distribution and potential field approach

Oil spill, may happen as a result of the offshore well vessel failures. The precise information about the location and real-time situation of the oil spill is essential to perform an efficient treatment of these environmental catastrophes. A novel approach of multi robot's system which can navigate autonomously and track oil spill on the sea surfaces. This system is able to self-adapt and path plan amidst environmental changes, including the temporospatial variation of the oil concentration. The method consists of two main parts, which are the modelling of the oil spill, the tracking system and autonomous control of the robots. The simulated model depicts the morphological complexities of the spatiotemporal changes in the oil spills. The fuzzy controller is designed to control the robots to control nonlinear and non-crisply distributed water surfaces where oil pollution occurs. Meanwhile, the multi-robot path planning system hybridised with artificial potential field approach to avoid the collision. Several numerical simulations with different scenarios are done to show the robustness of the methods, based on the accuracy and precision of tracking. The evaluation with the simulated ground truth demonstrates that accuracy and precision of the tracking system are more than 70 and 80 percent respectively.

Sensor Fusion-Based Cooperative Trail Following for Autonomous Multi-Robot System.

Autonomously following a man-made trail in the wild is a challenging problem for robotic systems. Recently, deep learning-based approaches have cast the trail following problem as an image classification task and have achieved great success in the vision-based trail-following problem. However, the existing research only focuses on the trail-following task with a single-robot system. In contrast, many robotic tasks in reality, such as search and rescue, are conducted by a group of robots. While these robots are grouped to move in the wild, they can cooperate to lead to a more robust performance and perform the trail-following task in a better manner. Concretely, each robot can periodically exchange the vision data with other robots and make decisions based both on its local view and the information from others. This paper proposes a sensor fusion-based cooperative trail-following method, which enables a group of robots to implement the trail-following task by fusing the sensor data of each robot. Our method allows each robot to face the same direction from different altitudes to fuse the vision data feature on the collective level and then take action respectively. Besides, considering the quality of service requirement of the robotic software, our method limits the condition to implementing the sensor data fusion process by using the “threshold” mechanism. Qualitative and quantitative experiments on the real-world dataset have shown that our method can significantly promote the recognition accuracy and lead to a more robust performance compared with the single-robot system.

Bio-inspired on-line path planner for cooperative exploration of unknown environment by a Multi-Robot System

This paper aims to present a cooperative and distributed navigation strategy, that is an on-line path planner, for an autonomous multi-robot system. The robots are intended to navigate and explore an unknown environment in order to find and reach obligatory passage points or way-points (goals), and then achieve a known final position. All robots in the team are homogeneous, independent and have limited communication skills. However they interact among them and with the environment to autonomously decide about their paths and tasks: if they should explore the environment, or avoid visiting a previously explored region, or to reach a discovered goal. Information sharing is directly carried out when the robots are into a communication area and/or indirectly by stigmergy. In this case, artificial pheromone, as a repulsive field, is used to mark regions that have already been explored by other members of the team, therefore avoiding redundant exploration and time waste. Fuzzy controllers are used for robots’ motion. The proposed on line path planner performance is evaluated in different simulated environment scenarios and the main results are presented.

Cooperative Transportation Motion Planning by Autonomous Multi Robot System

Cooperative Transportation Motion Planning by Autonomous Multi Robot System

The Utility of an Autonomous Multi-robot System of Underwater Floats

The underwater exploration of coastal seas is a challenging problem that requires a multi-vehicle system as an answer. The environment is presented along with the specific case of the Baltic Sea, as well as how its properties lead to requiring an autonomous group of robotic floats. The specifics of such a system are presented, detailing the cyclical and autonomous nature of its operation.

A homogeneous mobile robot team that is fault-tolerant

This paper introduces a design methodology of a fault-tolerant autonomous multi-robot system (MRS). An important fundamental topic for this type of system is the design of an on-line autonomous behavior acquisition mechanism that is capable of developing cooperative roles as well as assigning them to a robot appropriately in a noisy embedded environment. Our approach is to apply reinforcement learning that adopts the Bayesian discrimination method for segmenting a continuous state space and a continuous action space simultaneously. In addition, a neural network is provided for predicting the average of the other robots’ postures at the next time step in order to stabilize the reinforcement-learning environment. Computer simulations are conducted to illustrate the fault-tolerance of our MRS against a system change that occurs after the MRS achieves stable behavior.

強化学習を用いた自律マルチロボットシステムの協調行動獲得 : ロボット台数の増減に関する一考察(進化・学習とロボティクス3)

強化学習を用いた自律マルチロボットシステムの協調行動獲得 : ロボット台数の増減に関する一考察(進化・学習とロボティクス3)

Efficiency Assessment of Performance of Decentralized Autonomous Multi-Robot Systems

This paper presents a new methodology for the efficiency assessment of task performance of decentralized autonomous multi-robot system. This formulation considers the types of the robots (in terms of sensing, action, and control), the description of the environment (the world), the facts (rules) of the world, and the specifications of the tasks to be performed. The performance efficiency is defined in terms of the total time required for completing the task, total energy requirement, and the comparison of the final results and the desired results. A robot colony simulator was used to perform a number of experiments, measuring the task performance efficiency, of a colony of simulated robots which perform specific tasks in a virtual world. The experimental results are presented in this paper. This paper also describes a team of four robots designed and fabricated in hardware. The physical robots were used successfully to validate the results from the simulated colony.