Decentralized multi-robot encirclement of a 3D target with guaranteed collision avoidance

We present a control framework for achieving encirclement of a target moving in 3D using a multi-robot system. Three variations of a basic control strategy are proposed for different versions of the encirclement problem, and their effectiveness is formally established. An extension ensuring maintenance of a safe inter-robot distance is also discussed. The proposed framework is fully decentralized and only requires local communication among robots; in particular, each robot locally estimates all the relevant global quantities. We validate the proposed strategy through simulations on kinematic point robots and quadrotor UAVs, as well as experiments on differential-drive wheeled mobile robots.     

非完整机器人Leader-Follower编队控制器设计

编队控制是多机器人协作的最重要的研究领域,其目的是控制组中的机器人的相对位置和方向,让机器人移动作为一个整体。Le-ader-follower策略已经广泛地应用到多机器人系统编队控制中。文中涉及了非完整移动机器人leader-follower编队控制问题,然后描述了基于leader-follower策略的控制方法,最后采用输入/输出反馈线性化方法设计控制器,以确保编队的渐进稳定。在保持理想的相对距离和转向角时,该控制器能够有效地稳定编队。仿真结果表明了该编队控制方案的有效性。     

Multi-robot formation control using distance and orientation

Formation control analyses the convergence of a group of mobile agents to predefined geometric patterns. In traditional approaches, it is assumed that each agent knows the exact position of certain members of the group with respect to a reference frame and the associated control laws are designed according to inter-robot relative positions. Designing a more decentralized scheme, this paper proposes a formation scheme, using Lyapunov techniques, considering that the local controllers of the agents can be equipped with distance and orientation sensors. The main result of the paper applies to certain distance-based potential functions with inter-robot collision avoidance and an arbitrary undirected formation graph. Also, the control law includes an integral-type control that eliminates the effects of the dead-zone of actuators in order to avoid the standard techniques of normalization. The control approach is analyzed for omnidirectional robots with numerical simulations and extended for unicycle-type robots with real-time experiments.     

Cooperative exploration and protection of a workspace assisted by information networks

We develop strategies that enable multiple robots to cooperatively explore an unknown workspace while building information networks. Every robot deploys information nodes with sensing and communication capabilities while constructing the Voronoi diagram as the topological map of the workspace. The resulting information networks constructed by individual robots will eventually meet, allowing for inter-robot information sharing. The constructed information network is then employed by the mobile robots to protect the workspace against intruders. We introduce the intruder capturing strategy on the Voronoi diagram assisted by information networks.     

The NEXUS open system for integrating robotic software

In this paper a framework for constructing flexible, robust and efficient software applications for robots is described. The basic concepts needed to integrate complex, multidisciplinary robot software architectures are identified, and the methods to achieve them are taken from different areas of research (programming languages, network communication systems, real-time systems, etc.). The result is an open software system called NEXUS which includes the basic characteristics needed for the integration of very different software modules, minimizing the effort of integration and maximizing the reusability, efficiency and robustness of the resulting software applications. This software has proven to be a basis for more sophisticated tools that help in reducing the cost of modifications to and the complexity of multidisciplinary projects, allowing highly structured and reusable designs to be implemented. Although it has been currently implemented for mobile robots, it is a sufficiently generic framework suitable for use in other control systems.     

A Neural Network Approach to Dynamic Task Assignment of Multirobots

In this paper, a neural network approach to task assignment, based on a self-organizing map (SOM), is proposed for a multirobot system in dynamic environments subject to uncertainties. It is capable of dynamically controlling a group of mobile robots to achieve multiple tasks at different locations, so that the desired number of robots will arrive at every target location from arbitrary initial locations. In the proposed approach, the robot motion planning is integrated with the task assignment, thus the robots start to move once the overall task is given. The robot navigation can be dynamically adjusted to guarantee that each target location has the desired number of robots, even under uncertainties such as when some robots break down. The proposed approach is capable of dealing with changing environments. The effectiveness and efficiency of the proposed approach are demonstrated by simulation studies.     

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.     

Nonlinear formation control of unicycle-type mobile robots

We investigate formation control of a group of unicycle-type mobile robots at the dynamics level with a little amount of inter-robot communication. A combination of the virtual structure and path-tracking approaches is used to derive the formation architecture. Each individual robot has only position and orientation available for feedback. For each robot, a coordinate transformation is first derived to cancel the velocity quadratic terms. An observer is then designed to globally exponentially/asymptotically estimate the unmeasured velocities. An output feedback controller is designed for each robot. The controller is designed in such a way that the path derivative is left as a free input to synchronize the robots’ motion. Simulations illustrate the soundness of the proposed controller.     

Probabilistic Road Map sampling strategies for multi-robot motion planning

This paper presents a Probabilistic Road Map (PRM) motion planning algorithm to be queried within Dynamic Robot Networks—a multi-robot coordination platform for robots operating with limited sensing and inter-robot communication.

First, the Dynamic Robot Networks (DRN) coordination platform is introduced that facilitates centralized robot coordination across ad hoc networks, allowing safe navigation in dynamic, unknown environments. As robots move about their environment, they dynamically form communication networks. Within these networks, robots can share local sensing information and coordinate the actions of all robots in the network.

Second, a fast single-query Probabilistic Road Map (PRM) to be called within the DRN platform is presented that has been augmented with new sampling strategies. Traditional PRM strategies have shown success in searching large configuration spaces. Considered here is their application to on-line, centralized, multiple mobile robot planning problems. New sampling strategies that exploit the kinematics of non-holonomic mobile robots have been developed and implemented. First, an appropriate method of selecting milestones in a PRM is identified to enable fast coverage of the configuration space. Second, a new method of generating PRM milestones is described that decreases the planning time over traditional methods. Finally, a new endgame region for multi-robot PRMs is presented that increases the likelihood of finding solutions given difficult goal configurations.

Combining the DRN platform with these new sampling strategies, on-line centralized multi-robot planning is enabled. This allows robots to navigate safely in environments that are both dynamic and unknown. Simulations and real robot experiments are presented that demonstrate: (1) speed improvements accomplished by the sampling strategies, (2) centralized robot coordination across Dynamic Robot Networks, (3) on-the-fly motion planning to avoid moving and previously unknown obstacles and (4) autonomous robot navigation towards individual goal locations.     

Feedback control strategies for a nonholonomic mobile robot using a nonlinear oscillator

Among control problems for mobile robots, point‐to‐point stabilization is the most challenging since it does not admit designs with smooth static state feedback laws. Stabilization strategies for mobile robots, and nonholonomic systems generally, are smooth, time‐varying or nonsmooth, time‐invariant. Time‐varying control strategies are designed with umdamped linear oscillators but their fixed structure offer limited flexibility in control design. The central theme of this paper lies in use of nonlinear oscillators for mobile robot control. Large numbers of qualitatively different control strategies can be designed using nonlinear oscillators since stiffness and damping can be functions of robot states. We demonstrate by designing two fundamentally different controllers for two‐wheeled mobile robot using two variants of a particular nonlinear oscillator. First controller is dynamic and generates smooth control action. Second controller is almost‐smooth and time‐invariant. While first controller guarantees global asymptotic stability for any desired posture of robot, second controller is stable, and converges robot from almost any posture to desired posture. The only gap in posture space is unstable equilibrium manifold of measure zero. For both control strategies we mathematically establish stability and convergence of mobile robot to desired posture. Simulation results support theoretical claims. ©1999 John Wiley & Sons, Inc.     

A programming environment for real-time control of distributed multiple robotic systems

In recent years there has been great interest in robot software control architectures. However, although many interesting solutions have been presented, most of the research problems tackled related to a single robot perception, navigation and action in everyday environments. Instead, most of the practical applications of mobile robotics for service tasks in civilian environments consist of systems composed of multiple robots communicating with each other, with external sensing and actuating devices, and with external supervising workstations. RoboCup offers a great opportunity to deal with this problem. In fact the software architecture of a robot soccer player must allow successful intra-robot integration of the different activities (visual perception, path planning, strategy planning, motion control, etc.) spanning many different types of representation (raw sensor data, images, symbolic plans, etc.) and it must also guarantee successful inter-robot integration by supporting communication and cooperation. This paper focuses on this problem, presenting ETHNOS-IV - a programming environment for the design of a real-time control system composed of different robots, devices and external supervising or control stations - which has been successfully used within the Italian ART robot team in the RoboCup-99 competition. ETHNOS provides support from three main point of views which will be addressed in detail: inter-robot and intra-robot communication, realtime task scheduling, and software engineering and code reuse. Experimental results illustrating the advantages of this approach will also be presented.     

A switched-system approach to formation control and heading consensus for multi-robot systems

This paper proposes a novel, hybrid and decentralized, switched-system approach for formation and heading consensus control of mobile robots under switching communication topology, including collision avoidance capability. The set of robots consists of nonholonomic wheeled mobile robots and can include a teleoperated UAV. The key feature of this approach is a virtual graph, which is derived by adding a set of relative translation vectors to the real graph of the multiple robots. Our approach results in the robots in the real graph moving to the desired formation and achieving heading consensus while the virtual robots on the virtual graph reach pose consensus. If any robot detects a nearby obstacle or other robot, the robot will temporarily move along an avoidance vector, which is perpendicular and positively projected onto the attractive vector, such that collision is avoided while minimally deviating from its formation control path. Experimental results are provided by two different research groups to demonstrate the effectiveness of our approach. These experiments extend the theoretical development by introducing a teleoperated quadrotor as a leader robot of the multi-robot systems. The same control law works for the extended system, with no modifications.     

Editorial

The navigation capability of a group of robots can be improved by sensing of relative inter-robot positions and intercommunication of position estimates and planned trajectories. The cooperative navigation system (CNS) algorithm described here is based on a Kalman filter which uses inter-robot position sensing to update the collective position estimates of the group. Assuming independence of sensing and positioning errors, the CNS algorithm always improves individual robot estimates and the collective navigation performance improves as the number of robots increases. The CNS algorithm computation may be distributed among the robot group. Simulation results and experimental measurements on two Yamabico robots are described.     

Development of A Behavior‐Based Cooperative Search Strategy for Distributed Autonomous Mobile Robots Using Zigbee Wireless Sensor Network

To achieve efficient and objective search tasks in an unknown environment, a cooperative search strategy for distributed autonomous mobile robots is developed using a behavior‐based control framework with individual and group behaviors. The sensing information of each mobile robot activates the individual behaviors to facilitate autonomous search tasks to avoid obstacles. An 802.15.4 ZigBee wireless sensor network then activates the group behaviors that enable cooperative search among the mobile robots. An unknown environment is dynamically divided into several sub‐areas according to the locations and sensing data of the autonomous mobile robots. The group behaviors then enable the distributed autonomous mobile robots to scatter and move in the search environment. The developed cooperative search strategy successfully reduces the search time within the test environments by 22.67% (simulation results) and 31.15% (experimental results).     

Wheeled Mobile Robots Control in a Linear Platoon

Future transportation systems will require a number of drastic measures, mostly to lower traffic jams and air pollution in urban areas. Automatically guided vehicles capable of driving in a platoon fashion will represent an important feature of such systems. Platooning of a group of automated wheeled mobile robots relying on relative sensor information only is addressed in this paper. Each vehicle in the platoon must precisely follow the path of the vehicle in front of it and maintain the desired safety distance to that same vehicle. Vehicles have only distance and azimuth information to the preceding vehicle where no inter-vehicle communication is available. Following vehicles determine their reference positions and orientations based on estimated paths of the vehicles in front of them. Vehicles in the platoon are then controlled to follow the estimated trajectories. Then presented platooning control strategies are experimentally validated by experiments on a group of small-sized mobile robots and on a Pioneer 3AT mobile robot. The results and robustness analysis show the proposed platooning approach applicability.     

Region-based shape control for a swarm of robots

This paper presents a region-based shape controller for a swarm of robots. In this control method, the robots move as a group inside a desired region while maintaining a minimum distance among themselves. Various shapes of the desired region can be formed by choosing the appropriate objective functions. The robots in the group only need to communicate with their neighbors and not the entire community. The robots do not have specific identities or roles within the group. Therefore, the proposed method does not require specific orders or positions of the robots inside the region and yet different formations can be formed for a swarm of robots. A Lyapunov-like function is presented for convergence analysis of the multi-robot systems. Simulation results illustrate the performance of the proposed controller.     

A Graph Theoretic Approach for Modeling Mobile Robot Team Formations

This paper addresses a new approach for modeling and control of multiple teams of mobile robots navigating in a terrain with obstacles, while maintaining a desired formation and changing formations when required. We model each team as a triple, (g,r, ?? ), consisting of a group element, g∈SE(2), that describes the gross position of the lead robot, a set of shape variables, r, that describe the relative positions of robots, and a control graph, ??, that describes the behaviors of the robots in the formation. We assume that all the robots are equipped with the appropriate sensors to detect and avoid other robots and obstacles in the environment. Our framework enables the representation and enumeration of possible control graphs, and the coordination of transitions between any two control graphs. Further, we describe an algorithm that allows each team of robots to move between any two formations, while avoiding obstacles. As the number of robots increases, the number of possible control graphs increases. However, because the control computations are decentralized, the algorithms scale with the number of robots. We present examples to illustrate the control graphs and the algorithm for transitioning between them in the presence and absence of sensor noise. © 2002 Wiley Periodicals, Inc.     

基于机器人群的主动传感器网络自组织的运动规划

主动传感器网络的自组织通常要求移动节点群(机器人群)通过障碍物环境移动到指定地点后, 重新调整并按预定布局组网. 在网络的自组织过程中要保证每个移动节点(机器人)与整个网络之间的连通性. 在对移动机器人的保持连通性进行优化的基础上, 提出了单步位置预测与群体势场相结合的分布式运动规划方法进行主动传感器网络的部署和重置, 证明了机器人运动控制的稳定性和网络的连通性保持, 进行了有和无障碍物环境下超过40个机器人的仿真, 结果表明该方法适用于大规模的主动传感器网络重置, 并对不同规模的网络具有可扩展性.     

Analyzing the Multiple-target-multiple-agent Scenario Using Optimal Assignment Algorithms

This work considers the problem of maximum utilization of a set of mobile robots with limited sensor-range capabilities and limited travel distances. The robots are initially in random positions. A set of robots properly guards or covers a region if every point within the region is within the effective sensor range of at least one vehicle. We wish to move the vehicles into surveillance positions so as to guard or cover a region, while minimizing the maximum distance traveled by any vehicle. This problem can be formulated as an assignment problem, in which we must optimally decide which robot to assign to which slot of a desired matrix of grid points. The cost function is the maximum distance traveled by any robot. Assignment problems can be solved very efficiently. Solution times for one hundred robots took only seconds on a Silicon Graphics Crimson workstation. The initial positions of all the robots can be sampled by a central base station and their newly assigned positions communicated back to the robots. Alternatively, the robots can establish their own coordinate system with the origin fixed at one of the robots and orientation determined by the compass bearing of another robot relative to this robot. This paper presents example solutions to the multiple-target-multiple-agent scenario using a matching algorithm. Two separate cases with one hundred agents in each were analyzed using this method. We have found these mobile robot problems to be a very interesting application of optimal assignment algorithms, and we expect this to be a fruitful area for future research.     

基于达芬奇的移动机器人开发平台设计

针对传统移动机器人的实时性差和扩展性差的局限性,在达芬奇技术的基础上,通过裁减定制,去除冗余的功能,设计了一种移动机器人的开发平台。该机器人系统包括移动机器人需要的视觉系统,并有丰富的运动控制接口以及驱动模块。同时,设计了多传感器融合、无线网络通信、路径规划、运动控制、人机界面等移动机器人的测试软件和应用模块。该移动机器人平台也具有模块化、硬件体积小、功耗低、可移植、可扩展、实时性强等优点。