An algorithm for cooperative task allocation in scalable,constrained multiple robot systems

The current trends in the robotics field have led to the development of large-scale multiple robot systems, and they are deployed for complex missions. The robots in the system can communicate and interact with each other for resource sharing and task processing. Many of such systems fail despite the availability of necessary resources. The major reason for this is their poor coordination mechanism. Task planning, which involves task decomposition and task allocation, is paramount in the design of coordination and cooperation strategies of multiple robot systems. Task allocation mechanism allocates the task in a mission to the robots by maximizing the overall expected performance, and thereby reducing the total allocation cost for the team. In this paper, we formulate a heuristic search-based task allocation algorithm for the task processing in heterogeneous multiple robot system, by maximizing the efficiency in terms of both communication and processing cost. We assume a set of decomposed tasks of a mission, which needs to be allocated to the robots. The near-optimal allocation schemes are found using the proposed peer structure algorithm for the given problem, where the number of the tasks is more than the robots present in the system. The cost function is the summation of static overhead cost of robots, assignment cost, and the communication cost between the dependent tasks, if they are assigned to different robots. Experiments are performed to verify the effectiveness of the algorithm by comparing it with the existing methods in terms of computational time and quality of solution. The experimental results show that the proposed algorithm performs the best under different problem scales. This proves that the algorithm can be scaled for larger system and it can work for dynamic multiple robot system.     

Design of a modular assembly of four-footed robots with multiple functions

Modern industries use many types of robots. In addition to general robotic arms, bipedal, tripedal, and quadrupedal robots, which were originally developed as toys, are gradually being used for multiple applications in manufacturing processes. This research begins with establishing the platform for four-footed robots with multiple functions, high sensitivity, and modular assembly and this is how a fundamental model of the industrial robots is constructed. Under additional loads, the four feet of the quadrupedal robot reinforce its carrying ability and reliability compared to bipedal or tripedal robots, which helps it to carry more objects and enhances functionality. Based on different requirements and demands from the manufacturing processes, the highly sensitive four-footed robot provides an expandable interface to add different sensing components. In addition, when combined with a wireless communication module or independent 1.2 GHz radio frequency CCD wireless image transmission system, the user can control the robot remotely and instantly. The design helps the four-footed robot to expand its applications. By assembling and disassembling modules and changing the sensing components, the highly sensitive four-footed robot can be used for different tasks. Moreover, the remote control function of the robot will increase interaction with human beings, so it can become highly become involved in people's lives. The platform of the four-footed robot will become a design reference for the commercialization of different industrial robots, and it will provide the design of industrial robots with more options and useful applications.     

一个面向复杂任务的多机器人分布式协调系统

基于多智能体系统理论, 研究在非结构、不确定环境下面向复杂任务的多机器人分布式协调系统的实现原理、方法和技术. 提出的递阶混合式协调结构、基于网络的通讯模式和基于有限状态机的规划与控制集成方法, 充分考虑了复杂任务和真实自然环境的特点. 通过构建一个全实物的多移动机器人实验平台, 对规划、控制、传感、通讯、协调与合作的各关键技术进行了开发和集成, 使多机器人分布式协调技术的研究直接面向实际应用, 编队和物料搬运的演示实验结果展示了多机器人协调技术的广阔应用前景.     

Distributed multirobot exploration, mapping, and task allocation

We present an integrated approach to multirobot exploration, mapping and searching suitable for large teams of robots operating in unknown areas lacking an existing supporting communications infrastructure. We present a set of algorithms that have been both implemented and experimentally verified on teams—of what we refer to as Centibots—consisting of as many as 100 robots. The results that we present involve search tasks that can be divided into a mapping stage in which robots must jointly explore a large unknown area with the goal of generating a consistent map from the fragment, a search stage in which robots are deployed within the environment in order to systematically search for an object of interest, and a protection phase in which robots are distributed to track any intruders in the search area. During the first stage, the robots actively seek to verify their relative locations in order to ensure consistency when combining data into shared maps; they must also coordinate their exploration strategies so as to maximize the efficiency of exploration. In the second and third stages, robots allocate search tasks among themselves; since tasks are not defined a priori, the robots first produce a topological graph of the area of interest and then generate a set of tasks that reflect spatial and communication constraints. Our system was evaluated under extremely realistic real-world conditions. An outside evaluation team found the system to be highly efficient and robust.     

Complex Task Allocation in Mobile Surveillance Systems

In mobile surveillance systems, complex task allocation addresses how to optimally assign a set of surveillance tasks to a set of mobile sensing agents to maximize overall expected performance, taking into account the priorities of the tasks and the skill ratings of the mobile sensors. This paper presents a market-based approach to complex task allocation. Complex tasks are the tasks that can be decomposed into subtasks. Both centralized and hierarchical allocations are investigated as winner determination strategies for different levels of allocation and for static and dynamic search tree structures. The objective comparison results show that hierarchical dynamic tree task allocation outperforms all the other techniques especially in complex surveillance operations where large number of robots is used to scan large number of areas.     

Analysis of autonomous cooperative assembly using coordination schemes by heterogeneous robots using a control basis approach

Robotic technology is quickly evolving allowing robots to perform more complex tasks in less structured environments with more flexibility and autonomy. Heterogeneous multi-robot teams are more common as the specialized abilities of individual robots are used in concert to achieve tasks more effectively and efficiently. An important area of research is the use of robot teams to perform modular assemblies. To this end, this paper analyzed the relative performance of two robots with different morphologies and attributes in performing an assembly task autonomously under different coordination schemes using force sensing through a control basis approach. A rigid, point-to-point manipulator and a dual-armed pneumatically actuated humanoid robot performed the assembly of parts under a traditional “push-hold” coordination scheme and a human-mimicked “push-push” scheme. The study revealed that the scheme with higher level of cooperation—the “push-push” scheme—performed assemblies faster and more reliably, lowering the likelihood of stiction phenomena, jamming, and wedging. The study also revealed that in “push-hold” schemes industrial robots are better pushers and compliant robots are better holders. The results of our study affirm the use of heterogeneous robots to perform hard-to-do assemblies and also encourage humans to function as holder’s when working in concert with a robot assistant for insertion tasks.     

Altruistic coordination for multi-robot cooperative pathfinding

When multiple robots perform tasks in a shared workspace, they might be confronted with the risk of blocking each other’s ways, which will lead to conflicts or interference among them. Planning collision-free paths for all the robots is a challenge for a multi-robot system, which is also known as the multi-robot cooperative pathfinding problem in which each robot has to navigate from its starting location to the destination while keeping avoiding stationary obstacles as well as the other robots. In this paper, we present a novel fully decentralized approach to this problem. Our approach allows robots to make real-time responses to dynamic environments and can resolve a set of benchmark deadlock situations subject to complex spatial constraints in a shared workspace by means of altruistic coordination. Specifically, when confronted with congested situations, each robot can employ waiting, moving-forwards, dodging, retreating and turning-head strategies to make local adjustments. Most importantly, each robot only needs to coordinate and communicate with the others that are located within its coordinated network in our approach, which can reduce communication overhead in fully decentralized multi-robot systems. In addition, experimental results also show that our proposed approach provides an efficient and competitive solution to this problem.     

Development of multiple robotic fish cooperation platform

This article presents the development of a multiple robotic fish cooperation platform, which is established by employing a group of radio-controlled, multi-link fish-like robots. This work is inspired by the observation from nature that the capability of one single fish is limited, as in order to survive the atrocious circumstances in the sea, fish often swim in schools. The analogical situations occur in the robotic fish case. In engineering applications, most missions are so complex that they must be accomplished by effective cooperation of multiple fish robots. The platform presented in this article, as a novel test bed for multiple robotic fish cooperation, can be applied to different types of complex tasks. More importantly, it provides a good platform to test and verify all kinds of algorithms and strategies for cooperation of multiple underwater mobile robots. We use two cooperative tasks as examples to heuristically demonstrate the performance of this platform.     

群机器人通信研究综述

为了完成规定任务,群机器人中的个体机器人之间须进行协调合作,这有赖于机器人在有限感知和局部交互基础上的群体智能行为涌现,故对群机器人系统中的通信研究现状进行述评。首先对通信机制进行了划分,指出隐式通信的效率较显式通信为低,且作为人工系统的群机器人中更多采用显式通信机制。针对显式通信,通过对通信方式、网络拓扑结构、通信协议及通信语言等主要内容进行阐述,明确群机器人中通信研究的现状,并对该领域的研究方向进行了展望。     

CONRO: Towards Deployable Robots with Inter-Robots Metamorphic Capabilities

Metamorphic robots are modular robots that can reconfigure their shape. Such capability is desirable in tasks such as earthquake search and rescue and battlefield surveillance and scouting, where robots must go through unexpected situations and obstacles and perform tasks that are difficult for fixed-shape robots. The capabilities of the robots are determined by the design specification of their modules. In this paper, we present the design specification of a CONRO module, a small, self-sufficient and relatively homogeneous module that can be connected to other modules to form complex robots. These robots have not only the capability of changing their shape (intra-robot metamorphing) but also can split into smaller robots or merge with other robots to create a single larger robot (inter-robot metamorphing), i.e., CONRO robots can alter their shape and their size. Thus, heterogeneous robot teams can be built with homogeneous components. Furthermore, the CONRO robots can separate the reconfiguration stage from the locomotion stage, allowing the selection of configuration-dependent gaits. The locomotion and automatic inter-module docking capabilities of such robots were tested using tethered prototypes that can be reconfigured manually. We conclude the paper discussing the future work needed to fully realize the construction of these robots.