Educational training software for modelling and synthesis of controllers for robotic manipulators and robotized manufacturing cells

A general software system aimed at computer-aided design of controllers for robots and robotized technological systems is described in this paper. The software system includes modules for the synthesis of various levels of robot controller as well as controllers of complex robotized technological systems. The software includes simulation of robotic systems within manufacturing cells using various types of models: complete dynamic models, kinematic models and simple models in the form of finite automata. Using these modelsvarious algorithms for all controls levels in robot controllers may be synthesized taking into account the actual interaction between the robot and its environment. The software system enables the solution of the important problem of the interaction between higher and lower levels of controllers. Finally, a general purpose controller as a target system for the proposed software is described. The controller is designed as an open system allowing the user to apply various control laws and to run in conjunction with an actual robot. The general software system together with the controller represents a powerful educational tool in modern robotics.     

实时动态环境下多智能体的路径搜索研究

通过对实时动态环境下多智能体机器人足球中传球路线搜索的研究,提出了和双方队员控制区域有关的机动范围的概念及相应的计算方法,并用遗传算法解决了在搜索空间较大情况下的传球路线的搜索问题.实验和比赛结果证明,该方法能有效的解决实时动态环境下机器人足球中传球路线搜索的问题.􀁱 􀁽     

Fuzzy behavior-based control of mobile robots

An extensive fuzzy behavior-based architecture is proposed for the control of mobile robots in a multiagent environment. The behavior-based architecture decomposes the complex multirobotic system into smaller modules of roles, behaviors and actions. Fuzzy logic is used to implement individual behaviors, to coordinate the various behaviors, to select roles for each robot and, for robot perception, decision-making, and speed control. The architecture is implemented on a team of three soccer robots performing different roles interchangeably. The robot behaviors and roles are designed to be complementary to each other, so that a coherent team of robots exhibiting good collective behavior is obtained.     

Evolvable Hardware in Evolutionary Robotics

In recent decades the research on Evolutionary Robotics (ER) has developed rapidly. This direction is primarily concerned with the use of evolutionary computing techniques in the design of intelligent and adaptive controllers for robots. Meanwhile, much attention has been paid to a new set of integrated circuits named Evolvable Hardware (EHW), which is capable of reconfiguring its architectures unlimited time based on artificial evolution techniques. This paper surveys the application of evolvable hardware in evolutionary robotics. The evolvable hardware is an emerging research field concerning the development of evolvable robot controllers at the hardware level to adapt to dynamic changes in environments. The context of evolvable hardware and evolutionary robotics is reviewed, and a few representative experiments in the field of robotic hardware evolution are presented. As an alternative to conventional robotic controller designs, the potentialities and limitations of the EHW-based robotic system are discussed and summarized.     

RoboCup: robot world cup

RoboCup is an attempt to foster intelligent robotics research by providing a standard problem where a wide range of technologies can be integrated and examined. The First Robot World Cup Soccer Games and Conferences (RoboCup-97) was held during IJCAI-97, Nagoya, with over 40 teams participating from throughout the world. RoboCup soccer is a task for a team of fast-moving robots in a dynamic, noisy environment. In order for a robot team to actually perform a soccer game, various technologies must be incorporated including: design principles of autonomous agents, multi-agent collaboration, strategy acquisition, real-time reasoning, robotics, and sensor-fusion. This article describes technical challenges involved in RoboCup, its official rules, a report of RoboCup-97, and future perspectives     

Controlling gaze with an embodied interactive control architecture

Human-Robot Interaction (HRI) is a growing field of research that targets the development of robots which are easy to operate, more engaging and more entertaining. Natural human-like behavior is considered by many researchers as an important target of HRI. Research in Human-Human communications revealed that gaze control is one of the major interactive behaviors used by humans in close encounters. Human-like gaze control is then one of the important behaviors that a robot should have in order to provide natural interactions with human partners. To develop human-like natural gaze control that can integrate easily with other behaviors of the robot, a flexible robotic architecture is needed. Most robotic architectures available were developed with autonomous robots in mind. Although robots developed for HRI are usually autonomous, their autonomy is combined with interactivity, which adds more challenges on the design of the robotic architectures supporting them. This paper reports the development and evaluation of two gaze controllers using a new cross-platform robotic architecture for HRI applications called EICA (The Embodied Interactive Control Architecture), that was designed to meet those challenges emphasizing how low level attention focusing and action integration are implemented. Evaluation of the gaze controllers revealed human-like behavior in terms of mutual attention, gaze toward partner, and mutual gaze. The paper also reports a novel Floating Point Genetic Algorithm (FPGA) for learning the parameters of various processes of the gaze controller.     

Using direct competition to select for competent controllers in evolutionary robotics

Evolutionary robotics (ER) is a field of research that applies artificial evolution toward the automatic design and synthesis of intelligent robot controllers. The preceding decade saw numerous advances in evolutionary robotics hardware and software systems. However, the sophistication of resulting robot controllers has remained nearly static over this period of time. Here, we make the case that current methods of controller fitness evaluation are primary factors limiting the further development of ER. To address this, we define a form of fitness evaluation that relies on intra-population competition. In this research, complex neural networks were trained to control robots playing a competitive team game. To limit the amount of human bias or know-how injected into the evolving controllers, selection was based on whether controllers won or lost games. The robots relied on video sensing of their environment, and the neural networks required on the order of 150 inputs. This represents an order of magnitude increase in sensor complexity compared to other research in this field. Evolved controllers were tested extensively in real fully-autonomous robots and in simulation. Results and experiments are presented to characterize the training process and the acquisition of controller competency under different evolutionary conditions.     

Evolutionary robotics: the Sussex approach

We give an overview of evolutionary robotics research at Sussex over the last five years. We explain and justify our distinctive approaches to (artificial) evolution, and to the nature of robot control systems that are evolved. Results are presented from research with evolved controllers for autonomous mobile robots, simulated robots, co-evolved animats, real robots with software controllers, and a real robot with a controller directly evolved in hardware.     

Distributed Coordination in Heterogeneous Multi-Robot Systems

Coordination in multi-robot systems is a very active research field in Artificial Intelligence and Robotics, since through coordination one can achieve a more effective execution of the robots' tasks. In this paper we present an approach to distributed coordination of a multi-robot system that is based on dynamic role assignment. The approach relies on the broadcast communication of utility functions that define the capability for every robot to perform a task and on the execution of a coordination protocol for dynamic role assignment. The presented method is robust to communication failures and suitable for application in dynamic environments. In addition to experimental results showing the effectiveness of our approach, the method has been successfully implemented within the team of heterogeneous robots Azzurra Robot Team in a very dynamic hostile environment provided by the RoboCup robotic soccer competitions.     

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.     

Constraint-Based Design of Embedded Intelligent Systems

Substantial progress has been achieved using the standard Constraint Satisfaction Problem framework. However, there is a major unsolved challenge confronting the constraint research community: the constraint-based design of embedded intelligent systems. This requires a new online model of constraint satisfaction and new computational tools for specifying, modeling, verifying and implementing constraint-based, hybrid, intelligent systems, such as robots. The Constraint Net model of Zhang and Mackworth allows the design of hybrid intelligent systems as situated robots: modeling the robot and the environment symmetrically as dynamic systems. If the robot's perceptual and control systems are designed as constraint-satisfying devices then the total robotic system, consisting of the robot symmetrically coupled to the environment, can be proven correct. Some theoretical and practical advances based on this model are described, including experiments with the constraint-based design of robot soccer players.     

Real-time-based control system for a group of autonomous walking robots

The design target of complex control systems for novel robots with advanced motion abilities is to produce controllers (hardware and software) which are easy to program, re-program and debug. Those systems must be enabled to implement different motion principles with different hardware extensions (actuators, sensors, etc.). This paper introduces the problem of evaluation of hardware architecture together with the hardware type. We use the experience collected during realization of several prototypes of walking machines. The dedicated communication scheme elaborated for an embedded system is addressed in detail. The communication scheme can be used in every other system controlling the walking machine or controlling other robotic device. The navigation principles applied for a group of hexapods are briefly discussed for a better explanation of the functional structure of the implemented control system. The system actions are introduced. The system structure can be used for the control not only of a single mobile robot, but also a robot as a member of a group.     

Real-time control architecture using Xenomai for intelligent service robots in USN environments

This paper describes the implementation of a dual-kernel software architecture, based on standard Linux and real-time embedded Linux, for real-time control of service robots in ubiquitous sensor network environments. Mobile robots are used in active service for the assisted living of elderly people, monitoring their mental and physiological data with wireless sensor nodes. The data collected from sensor nodes are routed back to a sink node through multi-hop communication. The moving sink node installed on the main controller of the robot collects data and transmits it to the main controller. To be able to handle emergency situations, the robot needs to satisfy real-time requirements when processing the data collected, and invoking tasks to execute. This paper realizes a multi-hop sensor network and proposes real-time software architecture based on Xenomai. The real-time tasks were implemented, with priority, to rapidly respond to urgent sensor data. In order to validate the deterministic response of the proposed system, the performance measurements for the delay in handling the sensed data transmission and the trajectory control with a feedback loop were evaluated on the non real-time standard Linux.     

On-the-fly generation of multi-robot team formation strategies based on game conditions

This paper describes a new model to automatically generating dynamic formation strategies for robotic soccer applications based on game conditions, regarded to as favorable or unfavorable for a robotic team. Decisions are distributedly computed by the players of a multi-agent team. A game policy is defined and applied by a human coach who establishes the attitude of the team for defending or attacking. A simple neural net model is applied using current and previous game experience to classify the game’s parameters so that the new game conditions can be determined so that a robotic team can modify its strategy on-the-fly. Experiments and results of the proposed model for a robotic soccer team show the promise of the approach.     

Architecting centralized coordination of soccer robots based on principle solution

Coordination strategy is a relevant topic in multi-robot systems, and robot soccer offers a suitable domain to conduct research in multi-robot coordination. Team strategy collects and uses environmental information to derive optimal team reactions, through cooperation among individual soccer robots. This paper presents a diagrammatic approach to architecting the coordination strategy of robot soccer teams by means of a principle solution. The proposed model focuses on robot soccer leagues that possess a central decision-making system, involving the dynamic selection of the roles and behaviors of the robot soccer players. The work sets out from the conceptual design phase, facilitating cross-domain development efforts, where different layers must be interconnected and coordinated to perform multiple tasks. The principle solution allows for intuitive design and the modeling of team strategies in a highly complex robot soccer environment with changing game conditions. Furthermore, such an approach enables systematic realization of collaborative behaviors among the teammates.     

Design of robot control systems

An expository discussion on practical aspects of the design problems of robot control systems is presented. The first section discusses the present status of robot control methodology based on the so-called 'teaching and playback' control scheme. It is pointed out that PTP (point to point) control is still central in practice because only a sort of pulse-incremental servo controller is implemented for each joint actuator in actual industrial robots. The second section points out that servo controllers of this kind perform approximately as a PD or PID controller, and demonstrates that such PD and PID control schemes can work well even if the robot dynamics are non-linear and have strong couplings between the joint variables. The third section deals with path-tracking and trajectory-tracking control problems when teaching by human operators is not possible. This is then followed by a final but substantial section on recent results on learning control and adaptive control. An example of learning control for robot motions is given and its potential applicability in robotic systems is discussed.     

Development of CAM system based on industrial robotic servo controller without using robot language

This paper describes the development of a robotic CAM system for an articulated industrial robot RV1A from the view point of robotic servo controller. It is defined here that the CAM system includes an important function which allows an industrial robot to move along cutter location data (CL data) consisting of position and orientation components. In addition, the developed CAM system has a high applicability to other industrial robots whose servo systems are technically opened to end-users. The developed robotic CAM system works as a straightforward interface between a general CAD/CAM and an industrial robot. At the present stage, the relationship between CAD/CAM and industrial robots is not well established compared to NC machine tools that are widely spread in manufacturing industries. The CAM systems for NC machine tools are already established, however, the CAM system for industrial robots has not been sufficiently considered and developed yet. A teaching pendant is generally used to obtain position and orientation data of the arm tip before an industrial robot works. Here, in order to enhance the relationship between a conventional CAD/CAM system and an industrial robot, a simple and straightforward CAM system without using any robot language is developed and implemented. The basic design of the robotic CAM system and the experimental results are presented in this paper.     

A Real-Time Hybrid Architecture for Biped Humanoids with Active Vision Mechanisms

A real-time hybrid control architecture for biped humanoid robots is proposed. The architecture is modular and hierarchical. The main robot’s functionalities are organized in four parallel modules: perception, actuation, world-modeling, and hybrid control. Hybrid control is divided in three behavior-based hierarchical layers: the planning layer, the deliberative layer, and the reactive layer, which work in parallel and have very different response speeds and planning capabilities. The architecture allows: (1) the coordination of multiple robots and the execution of group behaviors without disturbing the robot’s reactivity and responsivity, which is very relevant for biped humanoid robots whose gait control requires real-time processing. (2) The straightforward management of the robot’s resources using resource multiplexers. (3) The integration of active vision mechanisms in the reactive layer under control of behavior-dependant value functions from the deliberative layer. This adds flexibility in the implementation of complex functionalities, such as the ones required for playing soccer in robot teams. The architecture is validated using simulated and real Nao humanoid robots. Passive and active behaviors are tested in simulated and real robot soccer setups. In addition, the ability to execute group behaviors in real- time is tested in international robot soccer competitions.     

5vs5仿真机器人足球比赛——防守算法研究

机器人足球赛是由硬件或仿真机器人进行的足球赛,文中涉及的仿真机器人足球赛在标准软件平台上进行。软件仿真比赛提供一个共用的服务程序作裁判,比赛双方程序通过网络协议和服务器进行连接,接受球场、足球和球员等相关实时信息,并做出自己的决策反馈给服务器。对多智能体之间的协作和协调进行了分析,论述了球队开发中整体防守和守门员防守的决策方法,以及这些方法在大连交通大学——梦想皆有神助（Dream）球队开发过程中的应用。在大连市第二届研究生仿真机器人足球大赛中Dream队获得了三等奖。     

Intelligent decision making in multi-agent robot soccer system through compounded artificial neural networks

This paper proposes a two-stage approach using artificial neural networks for the intelligent decision-making by the robots in a MiroSot small league. The first stage involves the use of an evolutionary algorithm for getting a rough estimate of the neural network weight matrices. The proposed approach is then generalized to the case of quick, intelligent and accurate decision-making in the case of a robot soccer system with robots utilizing the concept of compounded artificial neural networks. In the proposed approach a soccer field is divided into three zones so that the decision of the robots depends on the zone of the ball at any instant. The concept of a forward robot is also introduced in this paper to enhance the accuracy of the decision-making with the global strategy of advancing towards the goal area of the opponent for scoring a goal. Simulation results indicate that the proposed techniques are very effective in taking intelligent decision-making in a multi-agent robot soccer system in MiroSot small league as well as middle league.