Towards load-balanced de-congested multi-robotic agent traffic control by coordinated control at intersections

This paper presents a methodology for the coordination of multiple robotic agents moving from one location to another in an environment embedded with a network of agents, placed at strategic locations such as intersections. These intersection agents, communicate with robotic agents and also with each other to route robots in a way as to minimize the congestion, thus resulting in the continuous flow of robot traffic. A robot’s path to its destination is computed by the network (in this paper, ‘Network’ refers to the collection of ‘Network agents’ operating at the intersections) in terms of the next waypoints to reach. The intersection agents are capable of identifying robots in their proximity based on signal strength. An intersection agent controls the flow of agent traffic around it with the help of the data it collects from the messages received from the robots and other surrounding intersection agents. The congestion of traffic is reduced using a two-layered hierarchical strategy. The primary layer operates at the intersection to reduce the time delay of robots crossing them. The secondary layer maintains coordination between intersection agents and routes traffic such that delay is reduced through effective load balancing. The objective at the primary level, to reduce congestion at the intersection, is achieved through assigning priorities to pathways leading to the intersection based on the robot traffic density. At the secondary level, the load balancing of robots over multiple intersections is achieved through coordination between intersection agents by communication of robot densities in different pathways. Extensive comparisons show the performance gain of the current method over existing ones. Theoretical analysis apart from simulation show the advantages of load-balanced traffic flow over uncoordinated allotment of robotic agents to pathways. Transferring the burden of coordination to the network releases more computational power for the robots to engage in critical assistive activities.     

Toward combining autonomy and interactivity for social robots

The success of social robots in achieving natural coexistence with humans depends on both their level of autonomy and their interactive abilities. Although a lot of robotic architectures have been suggested and many researchers have focused on human–robot interaction, a robotic architecture that can effectively combine interactivity and autonomy is still unavailable. This paper contributes to the research efforts toward this architecture in the following ways. First a theoretical analysis is provided that leads to the notion of co-evolution between the agent and its environment and with other agents as the condition needed to combine both autonomy and interactivity. The analysis also shows that the basic competencies needed to achieve the required level of autonomy and the envisioned level of interactivity are similar but not the same. Secondly nine specific requirements are then formalized that should be achieved by the architecture. Thirdly a robotic architecture that tries to achieve those requirements by utilizing two main theoretical hypothesis and several insights from social science, developmental psychology and neuroscience is detailed. Lastly two experiments with a humanoid robot and a simulated agent are reported to show the potential of the proposed architecture.     

Multiagent control of self-reconfigurable robots

We demonstrate how multiagent systems provide useful control techniques for modular self-reconfigurable (metamorphic) robots. Such robots consist of many modules that can move relative to each other, thereby changing the overall shape of the robot to suit different tasks. Multiagent control is particularly well-suited for tasks involving uncertain and changing environments. We illustrate this approach through simulation experiments of Proteo, a metamorphic robot system currently under development.     

You, robot: on the linguistic construction of artificial others

How can we make sense of the idea of ‘personal’ or ‘social’ relations with robots? Starting from a social and phenomenological approach to human–robot relations, this paper explores how we can better understand and evaluate these relations by attending to the ways our conscious experience of the robot and the human–robot relation is mediated by language. It is argued that our talk about and to robots is not a mere representation of an objective robotic or social-interactive reality, but rather interprets and co-shapes our relation to these artificial quasi-others. Our use of language also changes as a result of our experiences and practices. This happens when people start talking to robots. In addition, this paper responds to the ethical objection that talking to and with robots is both unreal and deceptive. It is concluded that in order to give meaning to human–robot relations, to arrive at a more balanced ethical judgment, and to reflect on our current form of life, we should complement existing objective-scientific methodologies of social robotics and interaction studies with interpretations of the words, conversations, and stories in and about human–robot relations.     

From Fireflies to Fault-Tolerant Swarms of Robots

One of the essential benefits of swarm robotic systems is redundancy. In case one robot breaks down, another robot can take steps to repair the failed robot or take over the failed robot's task. Although fault tolerance and robustness to individual failures have often been central arguments in favor of swarm robotic systems, few studies have been dedicated to the subject. In this paper, we take inspiration from the synchronized flashing behavior observed in some species of fireflies. We derive a completely decentralized algorithm to detect non-operational robots in a swarm robotic system. Each robot flashes by lighting up its on-board light-emitting diodes (LEDs), and neighboring robots are driven to flash in synchrony. Since robots that are suffering catastrophic failures do not flash periodically, they can be detected by operational robots. We explore the performance of the proposed algorithm both on a real-world swarm robotic system and in simulation. We show that failed robots are detected correctly and in a timely manner, and we show that a system composed of robots with simulated self-repair capabilities can survive relatively high failure rates.      

Using Virtual Pheromones and Cameras for Dispersing a Team of Multiple Miniature Robots

To safely and efficiently guide personnel of search and rescue operations in disaster areas, swift gathering of relevant information such as the locations of victims, must occur. Using the concept of ‘repellent virtual pheromones’ inspired by insect colony coordination behaviors, miniature robots can be quickly dispersed to survey a disaster site. Assisted by visual servoing, dispersion of the miniature robots can quickly cover an area. An external observer such as another robot or an overhead camera is brought into the control loop to provide each miniature robot estimations of the positions of all of the other near-by robots in the robotic team. These miniature robots can then move away from the other near-by robots on the team, resulting in the robot collective becoming swiftly distributed through the local area. The technique has been simulated with differing pheromone persistence levels and implemented using the miniature Scout robots, developed by the Center for Distributed Robotics at the University of Minnesota, which are well-suited to surveillance and reconnaissance missions.     

Progressive autonomy: a method for gradually introducing autonomy into space missions

This paper presents a method under development for introducing autonomy and agent-based software into future space- and ground-based missions while both reducing the risk of mission failures and gaining the confidence and support of mission management and principal investigators (PIs). This is being done using a mechanism to support dynamic agent-community evolution (e.g., agents adapting to community changes, agents joining a community, or agents leaving a community). This dynamic capability of agents is necessary to achieve what we call ‘‘progressive autonomy,’’ which will allow dynamic modification of satellite systems using agent migration to update and modify spacecraft capabilities on an as-needed basis, as well as allow the introduction of mission management and autonomy into existing missions. This paper will also address an application of progressive autonomy through spectral analysis automation (SAA). The long-term fully realized SAA system will be a multiagent system designed to provide automated support for two major functions: (1) the automatic remote filtering (onboard a spacecraft or robotic device) of spectral image data based on PI guidance, goals, and science agenda and (2) the packing and transmission of the selected spectral data to the PI for further processing. Additionally, the innovative multiagent-based infrastructure for the SAA can be generalized in such a way as to enable it to support the type of progressive autonomy that will be needed to support an adaptive and growing autonomous behavior for other spacecraft or robotic subsystems.     

Dynamic computation offloading for ground and flying robots: Taxonomy,state of art,and future directions

The collaboration between ground and flying robots can take advantage of the capabilities of each system to enhance the performance of robotic applications, including military, healthcare, disaster management, etc. Unfortunately, this cooperation is restricted by the physical constraint that all computation should be performed on robots. The concept of computation offloading has great potential to improve the performance of both ground and flying robots. Unfortunately, external conditions like the network conditions, the robot’s mobility, and the availability of the processing resources may lead to new challenges. Accordingly, these challenges should be addressed from different perspectives, like security, network communication, response time, and energy consumption. Recently, most computation offloading solutions aim to optimize further the robot’s energy consumption. Several research works are designed 1.) to satisfy the real-time requirements of robotic applications and 2.) to solve the trade-off between the energy consumed by computation and communication. To better understand these concepts, we present a comprehensive overview of the computation offloading process for ground and flying robots. We also devised a taxonomy explaining the factors affecting the offloading decision in a robotic scenario. The taxonomy presents guidelines to recognize the scope of research in offloading decisions that were designed for robots. Then, we discuss the state-of-the-art techniques of computation offloading from an architectural point of view, and we survey works related to offloading decisions for robots.     

The CMUnited-98 champion small-robot team

Robotic soccer presents a large spectrum of challenging research opportunities. In this article, we present the main research and technical contributions of our champion CMUnited-98 small-robot team. The team is a multiagent robotic system with global perception, and distributed cognition and action. We introduce our new robot motion algorithm that reactively generates motion control to account for the target point, the desired robot orientation and obstacle avoidance. Our robots exhibit successful collision-free motion in the highly dynamic robotic soccer environment. At the strategic and decision-making level, we present the role-based behaviors of the CMUnited-98 robotic agents. Team collaboration is remarkably achieved through a new algorithm that allows for team agents to anticipate possible collaboration opportunities. Robots position themselves strategically in open positions that increase passing opportunities. The article terminates with a summary of the results of the RoboCup-98 games in which the CMUnited-98 small-robot team scored a total of 25 goals and suffered 6 goals in the five games that it played.     

Kilobot: A low cost robot with scalable operations designed for collective behaviors

In current robotics research there is a vast body of work on algorithms and control methods for groups of decentralized cooperating robots, called a swarm or collective. These algorithms are generally meant to control collectives of hundreds or even thousands of robots; however, for reasons of cost, time, or complexity, they are generally validated in simulation only, or on a group of a few tens of robots. To address this issue, this paper presents Kilobot, an open-source, low cost robot designed to make testing collective algorithms on hundreds or thousands of robots accessible to robotics researchers. To enable the possibility of large Kilobot collectives where the number of robots is an order of magnitude larger than the largest that exist today, each robot is made with only $14 worth of parts and takes 5 min to assemble. Furthermore, the robot design allows a single user to easily operate a large Kilobot collective, such as programming, powering on, and charging all robots, which would be difficult or impossible to do with many existing robotic systems. We demonstrate the capabilities of the Kilobot as a collective robot, by using a small robot test collective to implement four popular swarm behaviors: foraging, formation control, phototaxis, and synchronization.     

Human-robot teaming for search and rescue

This work establishes an architecture for Urban Search and Rescue and a methodology for mixing real-world and simulation-based testing. A sensor suite and sensor fusion algorithm for robust victim detection permits aggregation of sensor readings from various sensors on multiple robots. We have embarked on a research program focusing on the enabling technologies of effective USAR robotic rescue devices. The program is also researching system-level design, evaluation, and refinement of USAR rescue architectures that include teams of sensor-laden robots and human rescuers. In this paper, we present highlights from our research, which include our multiagent system (MAS) infrastructure, our simulation environment, and our approach to sensor fusion and interface design for effective robotic control.     

An active hybrid parallel robot for minimally invasive surgery

During the last years, there has been an increase in research in the field of medical robots. This trend motivated the development of a new robotics field called “robotic-assisted minimally invasive surgery”. The paper presents the kinematic and dynamic behavior of a parallel hybrid surgical robot PARASURG-9M. The robot consists of two subsystems: a surgical robotic arm, PARASURG 5M with five motors, and an active robotized surgical instrument PARASIM with four motors. The methodology for the robot kinematics is presented and the algorithm for robot workspace generation is described. PARASURG-9M inverse dynamic simulation is performed using MSC Adams and finally some numerical and simulation results of the developed experimental model with its system control are also described.     

PID landing orbit motion controller for an indoor blimp robot

Blimp robots are attractive as indoor flying robots because they can float in the air, land safely with low energy, and stay in motion for a long time compared with other flying robots. However, controlling blimp robots is difficult because they have nonlinear characteristics, are influenced by air streams, and can easily be influenced by inertia. Therefore, a robust and adaptive control system is needed for blimp robots. The applied research that has studied the features of indoor flying robots in recent years has prospered. Operating an indoor blimp robot for a long time is difficult because the payload is small, multiple batteries cannot be stacked, and the design of a thruster that gives freedom to the entire blimp robot is difficult. Therefore, an autonomous charge that allows operation for a long time is needed. We have developed a method of landing with orbital control of the charge point that gives autonomy to a blimp robot. The possibility of landing with orbital control is shown. This work was presented in part at the 10th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2005 An erratum to this article is available at .     

Robot football, artificial life, and complexity

Autonomous football-playing robots provide a stimulating research challenge in the sciences of complexity and artificial life. Currently, the game is dominated by problems of making the robots move sufficiently accurately. Even so, the dynamics of robot football are clearly chaotic, requiring some higher level control strategy. A mathematics of therelations between the robots, the ball, and the pitch is introduced. This mathematics supports a theory of structural time necessary for higher level dynamics and cognitive functions. In comparison with computer chess, robot football is more complex and may supplant it as a bench-mark test. Many systems considered to be complex have behaviour which emerges from interacting autonomous agents.Simulation is a new paradigm on which a science of such systems is being built. However, simulation currently suffers from the “can you trust it” syndrome: for many systems it is impractical to do experiments to test the simulation. However, robot football is a system which can be both simulated and built. It is suggested that this makes it an important scientific laboratory subject for understanding the relationship between simulation and real complex system behaviour. This work was presented, in part, at the Third International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–21, 1998     

Multiagent-Based Multi-team Formation Control for Mobile Robots

In the field of formation control, researchers generally control multiple robots in only one team, and little research focuses on multi-team formation control. In this paper, we propose an architecture, called Virtual Operator MultiAgent System (VOMAS), to perform formation control for multiple teams of mobile robots with the capabilities and advantages of scalability and autonomy. VOMAS is a hybrid architecture with two main agents. The virtual operator agent handles high level missions and team control, and the robot agent deals with low level formation control. The virtual operator uses four basic services including join, remove, split, and merge requests to perform multi-team control. A new robot can be easily added to a team by cloning a new virtual operator to control it. The robot agent uses a simple formation representation method to show formation to a large number of robots, and it uses the concept of potential field and behavior-based control to perform kinematic control to keep formation both in holonomic and nonholonomic mobile robots. In addition, we also test the stability, robustness, and uncertainty in the simulation. This research was supported by the National Science Council under grant NSC 91-2213-E-194-003.     

A methodology for design and analysis of cooperative behaviors with mobile robots

New methodologies are needed for modeling of physically cooperating mobile robots to be able to systematically design and analyze such systems. In this context, we present a method called the ‘P-robot Method’ under which we introduce entities called the p-robots at the environmental contact points and treat the linked mobile robots as a multiple degree-of-freedom object, comprising an articulated open kinematic chain, which is manipulated by the p-robots. The method is suitable to address three critical aspects of physical cooperation: a) analysis of environmental contacts, b) utilization of redundancy, and c) exploitation of system dynamics. Dynamics of the open chain are computed independent of the constraints, thus allowing the same set of equations to be used as the constraint conditions change, and simplifying the addition of multiple robots to the chain. The decoupling achieved through constraining the p-robots facilitates the analysis of kinematic as well as force constraints. We introduce the idea of a ‘tipping cone’, similar to a standard friction cone, to test whether forces on the robots cause undesired tipping. We have employed the P-robot Method for the static as well as dynamic analysis for a cooperative behavior involving two robots. The method is generalizable to analyze cooperative behaviors with any number of robots. We demonstrate that redundant actuation achieved by an adding a third robot to cooperation can help in satisfying the contact constraints. The P-robot Method can be useful to analyze other interesting multi-body robotic systems as well.     

Robotic Urban Search and Rescue: A Survey from the Control Perspective

Robotic urban search and rescue (USAR) is a challenging yet promising research area which has significant application potentials as has been seen during the rescue and recovery operations of recent disaster events. To date, the majority of rescue robots used in the field are teleoperated. In order to minimize a robot operator’s workload in time-critical disaster scenes, recent efforts have been made to equip these robots with some level of autonomy. This paper provides a detailed overview of developments in the exciting and challenging area of robotic control for USAR environments. In particular, we discuss the efforts that have been made in the literature towards: 1) developing low-level controllers for rescue robot autonomy in traversing uneven terrain and stairs, and perception-based simultaneous localization and mapping (SLAM) algorithms for developing 3D maps of USAR scenes, 2) task sharing of multiple tasks between operator and robot via semi-autonomous control, and 3) high-level control schemes that have been designed for multi-robot rescue teams.     

Design of robotic arm’s action to imitate the mechanism of an animal’s consciousness

We are attempting to develop a system so that a user is able to let robots perform an intellectual action that has a healing and friendly feeling. Based on the development process of the actions and consciousness of animals, we constructed a structure model which connects consciousness and action hierarchically, built a valuation function for action selection, and developed software to control the action of a robot. This software is called Consciousness-Based Architecture (CBA). With it, our aim is to connect a user and robot as closely as possible and to allow smooth communications between them by developing an emotional system that takes notice of consciousness. In our system, the robotic arm’s finger is outfitted with a small Web camera, which allows the arm to recognize external information so that the robot can select various actions that comply with certain factors in the outside environment. Furthermore, by using the actuator of the robotic arm, the system we have built provides a correspondence between the robot’s internal states, such as the degree of rotation angle, and the outside temperature. In the present study, a motivation model which considers the outside environment and the internal states has been built into the CBA, and the behavior of the robotic arm has been verified.     

基于KQML语言的多自主移动机器人仿真系统

用JAVA语言开发了栅格环境下的多自主移动机器人仿真系统,通过KQML语言通信模拟了多个自主的移动机器人,机器人的自主性主要体现在自主感知环境和自主进行路径规划、任务执行和安全导航等工作．该仿真系统具有平台无关性、地图无关性、算法无关性以及机器人配置的无关性,为多自主机器人系统的研究提供了一个可借鉴的平台．     

A frame-based knowledge software tool for developing interactive robots

A knowledge-based software tool for developing interactive robot applications, called SPAK, has been developed. The “world” of interest is represented in a SPAK knowledge base by using a frame knowledge technique. This technique is chosen because it can represent the world meaningfully and naturally. Relationships among frames, which represent things in the world, and actions to be taken when certain things occur can be specified. In action, SPAK perceives changes in the environment, updates the knowledge base if needed, and generates output actions according to the knowledge contents. To support robotic applications, extensions to the conventional frame model are proposed. Various robotic applications can run cooperatively on top of SPAK. Each can easily make use of the knowledge available, and share its knowledge with others. A SPAK knowledge editor allows simple and intuitive development and modification of robot applications. To demonstrate these benefits, a prototype system and a sample robot application are developed. A multiagent technique is employed to combine various robotic components, both hardware and software, together. A sample dialogue manager for managing interactions with humans runs as an application on SPAK.