The integration of dissimilar control architectures for mobile robot applications

This article discusses a dual architecture for autonomous mobile robots. The implementation application is an autonomous visual inspection system for waste stored in drums. We discuss the three main architectures commonly implemented on mobile robots. The various modules needed for the successful operation of a mobile robot are analyzed, and software and hardware requirements for each modules are noted. We make arguments as to which architecture is best suited for each component. From the results of this analysis, we propose a new dual architecture for autonomous mobile robots. Rather than developing a single hybrid architecture that has qualities of both behavioral and functional architectures, we have taken an approach that involves the integration of two distinct architectures. Next, we detail the implementation of the architecture of the robot, and the advantages of our architecture as it pertains to the integration of system components. System performance in the testing environment is discussed. © 1997 John Wiley & Sons, Inc.     

Agent主动目标的形式化模型

在agent结构中,主动目标是一个功能上自含且有自己独立控制流的实体.给出了主动目标相关的语法定义以及主动目标运行的操作语义,而且主动目标驱动下的BDI agent结构也被形式化地定义出来.区别于以往的一些BDI agent结构,目标不是隐含地表示而是作为实体显式地表示在agent结构中,使agent结构很自然地支持并行的目标,这被认为是agent理性行为的一个重要方面.此外,对目标的显式定义也为agent在动态的环境中对承诺的重新考虑带来了方便.     

PerAc: A neural architecture to control artificial animals

In this paper, we propose a new neural architecture called PerAc witch is a systematic way to decompose the control of an autonomous robot in perception and action flows. The PerAc architecture is used for the simulation of a vision system with a moving eye and then for landmark-based navigation on a mobile robot to learn without any a priori symbolic representation.     

INTELLIGENT BEHAVIOR IN MACHINES EMERGING FROM A COLLECTION OF INTERACTIVE CONTROL STRUCTURES

Control strategies that decompose the competence of an agent into independent, task-achieving control structures are emerging as viable alternatives to the notion that a robot is an explicit symbol processing device with input and output extensions in the form of sensors and actuators. This approach draws inspiration from ethology and the cognitive sciences, where the competence of biological creatures is seen to be a result of the successful combination of several distinct behavior patterns that enable them to interact effectively with their environments. The distinction between classical approaches that view intelligent behavior as the outcome of symbolic manipulations and an alternate approach that asserts that it is the careful integration of distributed, goal-competent control structures that lead to intelligent behavior is analyzed in detail. It is found that this dichotomy can be said to arise from the paradigm that is chosen to represent the knowledge at the disposal of the agent. Structurally encoded knowledge requiring an active interpreter for the knowledge to be exhibited in action leads to the symbol processing paradigm for intelligent behavior, whereas the interactive model for knowledge representation assumes that the knowledge at the disposal of an active agent resides within goal-competent, interactive control structures. A formalism is developed for representing the goal-directed nature of these interactive control structures with clear control-module boundaries. An implementation is then presented to demonstrate some of the basic features of this methodology.     

Toward a benchmarking framework for research into bio-inspired hardware-software artefacts

In this paper, we suggest that one of the more crucial tasks currently facing researchers into the field of autonomous mobile robotics is the provision of a common task, or set of tasks, as a means of evaluating different approaches to robot design and architecture, and the generation of a common set of experimental frameworks to facilitate these different approaches. This paper stars with a brief introduction to the field, and behavior-based control in particular. We then discuss the issue of animal versus robot behavior, and focus on simulated experimentation versus embodied robotics. Finally, we move to the feasibility of evaluating and benchmarking different architectures, with the aim of producing mobile robots of continuously higher utility, with specific reference to our current four-layered robot control architecture. This work was presented in part at the Fifth International Symposium on Artificial Life and Robotics, Oita, Japan, January 26–28, 2000     

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.     

矿用救援机器人控制体系结构研究

讨论了矿用救援机器人的工作环境及其控制体系结构的性能要求;介绍了目前已有的矿用救援机器人控制体系结构,包括基于工控机的闭式控制体系结构、基于PLC的分布式控制体系结构、基于工控机的分布式控制体系结构及基于嵌入式系统的分布式控制体系结构,分析了各种体系结构的优缺点;提出了一种基于嵌入式系统和CAN总线的分布式控制体系结构。该控制体系结构比目前已有的控制体系结构能更好地适应煤矿井下复杂的环境,特别适用于煤矿灾后救援。     

A multi-agent architecture with cooperative fuzzy control for a mobile robot

The challenges of robotics have led the researchers to develop control architectures composed of distributed, independent and asynchronous behaviors. One way to approach decentralization is through cooperative control, since it allows the development of complex behavior based on several controllers combined to achieve the desired result. Robots, however, require high-level cognitive capacities, and multi-agent architectures provide the appropriate level of abstraction to define them. This article describes a multi-agent architecture combined with cooperative control developed within the agent. The experiments were carried out on an ActivMedia Pioneer 2DX mobile robot.     

Dynamics of behavior: Theory and applications for autonomous robot architectures

Limitations both for the further development as well as for the actual technical application of autonomous robots arise from the lack of a unifying theoretical language. We propose three concepts for such a language: (1) Behaviors are represented by variables, specific constant values of which correspond to task demands; (2) Behaviors are generated as attractors of dynamical systems; (3) Neural field dynamics lift these dynamic principles to the representation of information. We show how these concepts can be used to design autonomous robots. Because behaviors are generated from attractor states of dynamical systems, design of a robot architecture addresses control-theoretic stability. Moreover, flexibility of the robot arises from bifurcations in the behavioral dynamics. Therefore techniques from the qualitative theory of dynamical systems can be used to design and tune autonomous robot architectures. We demonstrate these ideas in two implementations. In one case, visual sensory information is integrated to achieve target acquisition and obstacle avoidance in an autonomous vehicle minimizing the known problem of spurious states. In a second implementation of the same behavior, a neural dynamic field endows the system with a form of obstacle memory. A critical discussion of the approach highlights strengths and weaknesses and compares to other efforts in this direction.     

基于功能／行为集成的自主式移动机器人进化控制体系结构

本文针对自主式移动机器人控制体系结构中两类典型方法的不足,提出了一种进化控制体系 结构,实现了基于AI模型的方法与基于行为的方法的优势互补．文中阐述了进化控制的思想 ,并应用于移动机器人控制结构的设计．该结构使移动机器人具备良好的学习和适应能力、 较快的响应速度,同时拥有较好的理性和完成给定任务的能力．     

基于会话的安全、鲁棒共享控制方法

在共享控制系统中，比如智能服务机器人，操作员和自动化专门系统相互配合，共同控制．有效的共享控制需要复杂的系统体系结构，该结构可以提供安全鲁棒的运行，提供对用户友好的界面．满足这两项需求是一个不寻常的任务．介绍了解决这些问题的方法．首先给出一个以会话为中心采用面向代理编程和形式化方法的认知控制体系结构．采用混成设计的SharC认知控制体系结构，可以区分协同代理群体中每一个遥控设备的控制．安全性对共享控制系统来说是极为重要的，因此这种体系结构必须能够保证较高的安全性．最后，描述了作为控制系统核心的形式化建模会话管理器，通过示范平台中自动轮椅的例子说明这些不同的软件范例的应用。     

Cascade force control for autonomous beating heart motion compensation

Robotic-assisted heart surgeries do not allow autonomous compensation of cardiac motion. This paper tackles this problem, based on a robotic control architecture that relies on force feedback, without requiring vision data. The algorithm merges two cascade loops. The inner one is based on the Kalman active observer (AOB) for model-reference adaptive control and the outer one based on a model predictive control (MPC) approach generates control references for beating heart motion compensation. A 4-DoF surgical robot generates desired surgical forces and a 3-DoF robot equipped with an ex vivo heart at the end-effector reproduces realistic heart motion.     

A new system architecture for crowd simulation

Crowd simulation requires both rendering visually plausible images and managing the behavior of autonomous agents. Therefore, these applications need an efficient design that allows them to simultaneously handle these two requirements. Although several proposals have focused on the software architectures for these systems, no proposals have focused on the computer systems supporting them.In this paper, we analyze the computer architectures used in the literature to support distributed virtual environments. Also, we propose a distributed computer architecture which is efficient enough to support simulations of thousand of autonomous agents. This proposal consists of a cluster of interconnected computers in order to improve flexibility and robustness, as well as a hierarchical software architecture that efficiently provides consistency. Performance evaluation results show that the trade-off between flexibility and consistency allows to efficiently manage thousands of autonomous agents. Therefore, this network-based system architecture can provide the required scalability for large-scale crowd simulations.     

A new mobile robot control approach via fusion of control signals.

This paper proposes an alternative approach to address the problem of coordinating behaviors in mobile robot navigation: fusion of control signals. Such approach is based on a set of two decentralized information filters, which accomplish the data fusion involved. Besides these two fusion engines, control architectures designed according to this approach also embed a set of different controllers that generate reference signals for the robot linear and angular speeds. Such signals are delivered to the two decentralized information filters, which estimate suitable overall reference signals for the robot linear and angular speeds, respectively. Thus, the background for designing such control architectures is provided by the nonlinear systems theory, which makes this approach different from any other yet proposed. This background also allows checking control architectures designed according to the proposed approach for stability. Such analysis is carried out in the paper, and shows that the robot always reaches its final destination, in spite of either obstacles along its path or the environment layout. As an example, a control architecture is designed to guide a mobile robot in an experiment, whose results allows checking the good performance of the control architecture and validating the design approach proposed as well.     

通过协同模型取得分布式系统的适应性

针对分布式系统中自治实体的交互行为和实时约束行为动态变化的问题,提出了一个具有动态性、实时性的协同模型.在该模型中,利用关注点分离思想,从传统自治实体中分离出两类不同的活动实体,即负责完成实时行为的时控协调器和协调活动交互的通信协调器,解决了开放分布环境下分布式系统的适应性和动态性问题.最后,利用Java消息服务技术和E JB技术实现了模型,并给出了在汽车导航系统中的一个应用实例.     

End-user programming architecture facilitates the uptake of robots in social therapies

This paper proposes an architecture that makes programming of robot behavior of an arbitrary complexity possible for end-users and shows the technical solutions in a way that is easy to understand and generalize to different situations. It aims to facilitate the uptake and actual use of robot technologies in therapies for training social skills to autistic children. However, the framework is easy to generalize for an arbitrary human–robot interaction application, where users with no technical background need to program robots, i.e. in various assistive robotics applications. We identified the main needs of end-user programming of robots as a basic prerequisite for the uptake of robots in assistive applications. These are reusability, modularity, affordances for natural interaction and the ease of use. After reviewing the shortcomings of the existing architectures, we developed an initial architecture according to these principles and embedded it in a robot platform. Further, we used a co-creation process to develop and concretize the architecture to facilitate solutions and create affordances for robot specialists and therapists. Several pilot tests showed that different user groups, including therapists with general computer skills and adolescents with autism could make simple training or general behavioral scenarios within 1 h, by connecting existing behavioral blocks and by typing textual robot commands for fine-tuning the behaviors. In addition, this paper explains the basic concepts behind the TiViPE based robot control platform, and gives guidelines for choosing the robot programming tool and designing end-user platforms for robots.     

自主机器人自组织结构IRASO的仿真研究

自主机器人车辆具有智能性和快速反应的特点,而在精确推理和实时性之间录示最佳折衷是体系结构的关键文中提出基于分布式多Ａｇｅｎｔ系统的自组织体系结构ＩＲＡＳＯ系统的自组织体系结构ＩＲＡＳＯ,Ａｇｅｎｔ之间动态组合以适应环境变化,公告板系统评估环境势态和指导Ａｇｅｎｔ组织,同时设计了Ａｇｅｎｔ协调工作的空间和时间模型,基于ＴＣＰ／ＩＰ的计算联勇域为异质分布式多Ａｇｅｎｔ的协作运行提供支持,仿真结果表明该     

An Autonomous Spacecraft Agent Prototype

This paper describes the New Millennium Remote Agent (NMRA) architecture for autonomous spacecraft control systems. The architecture supports challenging requirements of the autonomous spacecraft domain not usually addressed in mobile robot architectures, including highly reliable autonomous operations over extended time periods in the presence of tight resource constraints, hard deadlines, limited observability, and concurrent activity. A hybrid architecture, NMRA integrates traditional real-time monitoring and control with heterogeneous components for constraint-based planning and scheduling, robust multi-threaded execution, and model-based diagnosis and reconfiguration. Novel features of this integrated architecture include support for robust closed-loop generation and execution of concurrent temporal plans and a hybrid procedural/deductive executive.We implemented a prototype autonomous spacecraft agent within the architecture and successfully demonstrated the prototype in the context of a challenging autonomous mission scenario on a simulated spacecraft. As a result of this success, the integrated architecture has been selected to fly as an autonomy experiment on Deep Space One (DS-1), the first flight of NASA';s New Millennium Program (NMP), which will launch in 1998. It will be the first AI system to autonomously control an actual spacecraft.     

Dynamic Behavior Sequencing for Hybrid Robot Architectures

Hybrid robot control architectures separate planning, coordination, and sensing and acting into separate processing layers to provide autonomous robots both deliberative and reactive functionality. This approach results in systems that perform well in goal-oriented and dynamic environments. Often, the interfaces and intents of each functional layer are tightly coupled and hand coded so any system change requires several changes in the other layers. This work presents the dynamic behavior hierarchy generation (DBHG) algorithm, which uses an abstract behavior representation to automatically build a behavior hierarchy for meeting a task goal. The generation of the behavior hierarchy occurs without knowledge of the low-level implementation or the high-level goals the behaviors achieve. The algorithm’s ability to automate the behavior hierarchy generation is demonstrated on a robot task of target search, identification, and extraction. An additional simulated experiment in which deliberation identifies which sensors to use to conserve power shows that no system modification or predefined task structures is required for the DBHG to dynamically build different behavior hierarchies.