DYLEMA: Using walking robots for landmine detection and location

Detection and removal of antipersonnel landmines is an important worldwide concern. A huge number of landmines has been deployed over the last twenty years, and demining will take several more decades, even if no more mines were deployed in future. An adequate mine-clearance rate can only be achieved by using new technologies such as improved sensors, efficient manipulators and mobile robots. This paper presents some basic ideas on the configuration of a mobile system for detecting and locating antipersonnel landmines efficiently and effectively. The paper describes the main features of the overall system, which consists of a sensor head that can detect certain landmine types, a manipulator to move the sensor head over large areas, a locating system based on a global-positioning system, a remote supervisor computer and a legged robot used as the subsystems’ carrier. The whole system has been configured to work in a semi-autonomous mode with a view also to robot mobility and energy efficiency.     

The NIST Real-time Control System (RCS): an approach to intelligent systems research

Differences between the deliberative and reactive aspects of behaviour have led to different scientific approaches that have divided the field of cognitive research for at least a century. In the tradition of the behaviourist school of psychology, many present day researchers in advanced robotics and artificial intelligence have abandoned inquiry into the complexities of cognitive behaviour in favour of a minimalist philosophy that focuses primarily on stimulus-response reactivity. In contrast, the Real-time Control System (RCS) developed at NIST and elsewhere over the past two decades provides a model for bridging the gap between deliberative and reactive behaviours. RCS is a reference model architecture for intelligent systems design that consists of a hierarchically layered set of processing nodes. In each node, there are both cognitive and reactive elements. At each layer, entities are recognized, tasks are deliberatively planned, and feedback from sensors closes a reactive control loop. RCS thus integrates and distributes deliberative and reactive functions throughout the entire hierarchical architecture, at all levels and time frames. A comparison is made between RCS and subsumption and some illustrative examples of RCS applications are given.     

Flexible real-time mobile robotic architecture based on behavioural models

Behaviour-based models have been widely used to represent mobile robotic systems, which operate in uncertain dynamic environments and combine information from several sensory sources. The specification of complex mobile robotic applications is performed in such models by combining deliberative goal-oriented planning with reactive sensor driven operations. Consequently, the design of mobile robotic architectures requires the combination of time-constrained activities with deliberate time-consuming components. Furthermore, the temporal requirements of the reactive activities are variable and dependent on the environment (i.e. recognition processes) and/or on application parameters (i.e. process frequencies depend on robot speed).In this paper, a real-time mobile robotic architecture to cope with the functional and variable temporal characteristics of behaviour-based mobile robotic applications is proposed. Run-time flexibility is a main feature of the architecture that supports the variability of the temporal characteristics of the workload. The system has to be adapted to the environmental conditions, by adjusting robot control parameters (i.e. speed) or the system load (i.e. computational time), and take actions depending on it. This influence is focused on the ability of the system to select the appropriate activity to be executed depending on the available time, and, to change its behaviour depending on the environmental information. The flexibility of the system is allowed thanks to the definition of a real-time task model and the design of adaptation mechanisms for the regulation of the reactive load.The improvement of the robot quality of service (QoS) is another important aspect discussed in the paper. The architecture incorporates a quality of service manager (QoSM) that allows dynamically monitor analyse and improve the robot performances. Depending on the internal state, on the environment and on the objectives, the robot performance requirements vary (i.e. when the environment is overloaded, global map processes generating high-quality maps are required). The QoSM receives the performance requirements of the robot, and by adjusting the reactive load, the system enables the necessary slack time to schedule the more suitable deliberative processes and hence fulfilling the robot QoS. Moreover, the deliberative load can be scheduled by different heuristic strategies that provide answers of varying quality.     

Development of a real-time control architecture for a semi-autonomous underwater vehicle for intervention missions

The need for autonomous underwater vehicles (AUVs) for intervention missions becomes greater as they can perform underwater tasks requiring physical contacts with the underwater environment, such as underwater plug-in/plug-out, construction and repair, cable streaming, mine hunting, munitions retrieval, and scientific sampling. This paper describes a semi-autonomous underwater vehicle for intervention missions that has multiple on-board CPUs, redundant sensors and actuators, on-board power source and a robotic manipulator for dextrous underwater performance. Such a complex robotic vehicle system requires advanced control software architecture for on-board intelligence with a wide range of sensors and actuators to carry out required missions. In this paper, AUV control architectures are reviewed and a sensor data bus based control architecture (SDBCA) is presented. SDBCA is a modified hierarchical architecture that offers good controllability and stability while sensor data bus increases flexibility of system design, making it possible to have a prompt response from high-level control with respect to low-level sensor data. The overall sensor input mechanism of SDBCA becomes similar to the sensor input mechanism of subsumption architecture.     

A Flexible Control Architecture for Mobile Robots: An Application for a Walking Robot

To get the best features of both deliberative and reactive controllers, present mobile robot control architectures are designed to accommodate both types of controller. However, these architectures are still very rigidly structured thus deliberative modules are always assigned to the same role as a high-level planner or sequencer while low-level reactive modules are still the ones directly interacting with the robot environment. Furthermore, within these architectures communication and interface between modules are if not strongly established, they are very complex thus making them unsuitable for simple robotic systems. Our idea in this paper is to present a control architecture that is flexible in the sense that it can easily integrate both reactive and deliberative modules but not necessarily restricting the role of each type of controller. Communication between modules is through simple arbitration schemes while interface is by connecting a common communication line between modules and simple read and/or write access of data objects. On top of these features, the proposed control architecture is scalable and exhibits graceful degradation when some of the modules fail, similar to the present mobile robot architectures. Our idea has enabled our four-legged robot to walk autonomously in a structured uneven terrain.     

一种实时Agent体系结构

提出了一种应用于实时环境的Agent体系结构,集成了慎思式和反应式Agent的主要行为特征,支持多Agent之间的协同求解,并在内部机制上采用集中控制和规划缓冲等技术满足系统对实时性和稳定性的需要。最后给出了该体系结构在实时监控系统中的一个具体应用,论证了其设计的合理性。     

Sensor scheduling in mobile robots using incomplete information via Min-Conflict with Happiness.

This paper develops and applies a variant of the Min-Conflict algorithm to the problem of sensor allocation with incomplete information for mobile robots. A categorization of the types of contention over sensing resources is provided, as well as a taxonomy of available information for the sensor scheduling task. The Min-Conflict with Happiness (MCH) heuristic algorithm, which performs sensor scheduling for situations in which no information is known about future assignments, is then described. The primary contribution of this modification to Min-Conflict is that it permits the optimization of sensor certainty over the set of all active behaviors, thereby producing the best sensing state for the robot at any given time. Data are taken from simulation experiments and runs from a pair of Nomad200 robots using the SFX hybrid deliberative/reactive architecture. Results from these experiments demonstrate that MCH is able to satisfy more sensor assignments (up to 142%) and maintain a higher overall utility of sensing than greedy or random assignments (a 7-24% increase), even in the presence of sensor failures. In addition, MCH supports behavioral sensor fusion allocations. The practical advantages of MCH include fast, dynamic repair of broken schedules allowing it to be used on computationally constrained systems, compatibility with the dominant hybrid robot architectural style, and least-disturbance of prior assignments minimizing interruptions to reactive behaviors.     

Biasing behavioral activation with intent for an entertainment robot

Deliberate control of an entertainment robot presents a special problem in balancing the requirement for intentional behavior with the existing mechanisms for autonomous action selection. It is proposed that the intentional biasing of activation in lower-level reactive behaviors is the proper mechanism for realizing such deliberative action. In addition, it is suggested that directed intentional bias can result in goal-oriented behavior without subsuming the underlying action selection used to generate natural behavior. This objective is realized through a structure called the intentional bus. The intentional bus serves as the interface between deliberative and reactive control by realizing high-level goals through the modulation of intentional signals sent to the reactive layer. A deliberative architecture that uses the intentional bus to realize planned behavior is described. In addition, it is shown how the intentional bus framework can be expanded to support the serialization of planned behavior by shifting from direct intentional influence for plan execution to attentional triggering of a learned action sequence. Finally, an implementation of this architecture, developed and tested on Sony’s humanoid robot QRIO, is described.     

Microcontroller-operated anthropomorphic manipulator with haptic feedback

This article presents the design of a cluster-distributed computing system to operate and control an anthropomorphic manipulator with haptic feedback. The system hardware consists of four major building blocks, anthropomorphic manipulator, haptic sensor glove, real-time microcontroller-based cluster distributed computing (CDC) network, and closed-loop controller. The system software architecture consists of three key operation modules, namely, the sensor glove, anthropomorphic manipulator and communication module. It is designed based on a shared file system concept which forms the foundation of the CDC protocol. The key advantages of this system are its novel structure and its comparatively low cost using microcontroller-based distributed cluster networks which allow large-scale expansion/integration.     

Touring Machines: autonomous agents with attitudes

A multilayered integrated architecture for controlling autonomous mobile agents, or Touring Machines, is introduced. This architecture combines capabilities for producing a range of reactive and deliberative behaviors in dynamic, unpredictable domains. The approach is influenced by recent work on reactive and behavior-based agent architectures. Touring Machines blend sophisticated and simplified control features. Experience shows that this layered architecture can be configured to behave with robustness and flexibility simultaneously in dynamic settings. The implementation of the control architecture on a testbed is reported     

一种混合结构的移动机器人导航控制策略

研究了未知环境下移动机器人实时的导航控制问题.采用分布式系统将反射式行为、反应式行为与慎思规划相结合,设计了移动机器人导航控制策略.根据激光雷达传感器信息设计了基于栅格的实时避障算法和解锁策略.通过慎思规划解决了复杂环境下的局部势能陷阱问题.通过自行研制的移动机器人IMR01的实验验证了导航策略的有效性.     

一种新的基于Agent的体系结构

Agent体系结构是由理论研究向系统实现的关键一步。首先,在Agent特性分析和形式化描述的基础上,阐述了Agent的层次概念框架。然后,研究SubSumption,BDI和GRATE等典型结构特点,比较了反应式和慎思式两种体系结构,反应式Agent和慎思式Agent体系结构各有优劣。确立采用分层式混合结构的设计思想,并结合Agent的特性,从信息流和控制流的角度来刻画更为复杂的层次结构。在此基础上,设计了一种带序列池（POOL）的二维混合体系结构,并对其实现机制进行了深入研究。在不增加系统复杂性的前提下,提高系统的效率和能力。     

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.     

文献扫描机器人多关节机械臂滑膜控制系统设计

为提升机器人机械臂关节的传动性能,使其处于良好的反步自适应工作环境,设计文献扫描机器人多关节机械臂滑膜控制系统。利用关键控制电路,实现机械臂全局PID滑膜控制器与机器人多关节滑膜控制器间的定向连接,完成新型控制系统的硬件运行环境搭建。通过机器人控制传感器标定操作,建立等效控制及动态滑膜方程,并利用上述计算结果界定机械臂滑膜的动态品质,实现新型控制系统的软件运行环境搭建,结合软、硬件运行单元,完成文献扫描机器人多关节机械臂滑膜控制系统设计。模拟文献扫描机器人多关节机械臂运行状态,设计对比实验结果表明,与传统系统相比应用新型滑膜控制系统后,机械臂关节的传动能力得到有效提升,反步自适应参数最大值可达到1.70     

AuRA: principles and practice in review

This paper reviews key concepts of the Autonomous Robot Architecture (AuRA). Its structure, strengths, and roots in biology are presented. AuRA is a hybrid deliberative/ reactive robotic architecture that has been developed and refined over the past decade. In this article, particular focus is placed on the reactive behavioural component of this hybrid architecture. Various real world robots that have been implemented using this architectural paradigm are discussed, including a case study of a multiagent robotic team that competed and won the 1994 AAAI Mobile Robot Competition.     

一种混合Agent体系结构及决策算法

提出的混合Agent体系结构包括反应式结构和慎思结构，反应式结构提高Agent的反应性，慎思结构增强Agent的智能性；为了提高智能体决策的速度和智能性。提出一种新颖的Agent决策算法。该文提出的混合Agent体系结构及决策算法已成功地应用到RoboCup仿真机器人系统中，仿真结果说明了该结构和算法的有效性。     

Three-dimensional shape recognition method using ultrasonics for manipulator control system

This article describes a three-dimensional shape recognition method that employs an ultrasonic distance sensor mounted on a manipulator, and its application to a manipulator control system. The principle of the method is to reconstruct an object surface numerically using both distance and orientation informations of an object. The method makes it possible to control the manipulator, to set the sensor in any position and orientation employing freedom of the manipulator, and to measure the object. The method is available for manipulator control because it can precisely assess the distance from the manipulator to the object, as well as reconstruct the object shape. Experimental results show that the newly developed method make object shape recognition easy and inexpensive. Application experiment proved that the method is effective for manipulator work due to its provision of distance information.     

Robot Navigation by Waypoints

In this paper we propose a novel waypoint-based robot navigation method that combines reactive and deliberative actions. The approach uses reactive exploration to generate waypoints that can then be used by a deliberative system to plan future movements through the same environment. The waypoints are used largely to provide the interface between reactive and deliberative navigation and a range of methods could be used for either type of navigation. In the current work, an incremental decision tree method is used to navigate the robot reactively from the specified initial position to its destination avoiding obstacles in its path and a genetic algorithm method is used to perform the deliberative navigation. The new method is shown to have a number of practical advantages. Firstly, in contrast with many deliberative approaches, complete knowledge of the environment is not required, nor is it necessary to make assumptions regarding the geometry of obstacles. Secondly, the presence of a reactive navigator means it is always possible to continue directed movements in unknown or changing environments or when time constraints become particularly demanding. Thirdly, the use of waypoints allows escape from certain obstacle configurations that would normally trap robots navigated under the control of purely reactive methods. In addition, the results presented in this paper from a number of realistic simulated environments show that the adoption of waypoints significantly reduces the time to calculate a deliberative path.     

Belief-Driven Manipulator Visual Servoing for Less Controlled Environments

This paper presents the architecture of a feedforward manipulator control strategy based on a belief function that may be appropriate for less controlled environments. In this architecture, the belief about the environmental state, as described by a probability density function, is maintained by a recursive Bayesian estimation process. A likelihood is derived from each observation regardless of whether the targeted features of the environmental state have been detected or not. This provides continuously evolving information to the controller and allows an inaccurate belief to evolve into an accurate belief. Control actions are determined by maximizing objective functions using non-linear optimization. Forward models are used to transform control actions to a predicted state so that objective functions may be expressed in task space. The first set of examples numerically investigates the validity of the proposed strategy by demonstrating control in a two dimensional scenario. Then a more realistic application is presented where a robotic manipulator executes a searching and tracking task using an eye-in-hand vision sensor.     

Real-time trajectory generation in multi-RCCL

This article describes the design of the trajectory generator for a robot programming system called Multi-RCCL, which is a package of “C” routines for doing real-time manipulator control in a UNIX environment. RCCL has been used successfully in developing robot control applications in numerous research and industry facilities over the last several years. One of its strongest features is the ability to integrate real-time sensor control into the manipulator task specification. RCCL primitives supply the trajectory generator with target points for motions in joint or Cartesian coordinates. Other primitives allow the code developer to specify on-line functions that can modify the target points, or possibly cancel motion requests, in response to various sensor or control inputs. The design requirements of the trajectory generator are that it be able to integrate these on-line modifications into the overall robot motion and provide a smooth path between adjacent motions even when sensor inputs make the future trajectory uncertain. © 1993 John Wiley & Sons, Inc.