An intelligent dental robot

An intelligent dental robot (IDR) is reported for the purpose of artificial denture verification and test. Methods: The IDR is composed of power system, intelligent control and driving system, sensor system and supporting system. Five Maxon motors are adopted to provide the driving force for the IDR. Novel motor linear actuators are developed to mimic the movement of human’s masticatory muscles. Forward and inverse kinematics of the IDR are analyzed. Seven high-precision pressure sensors are utilized to detect the force on individual artificial tooth. Results: Motion and force experiments are conducted on the IDR. The maximum biting force provided by the IDR is 490?N. Hysteresis rate of the biting force loading and unloading is less than 3%. The largest displacement for the mandible movement test is found to be 60, 9 and 22?mm in the vertical, protrusive and lateral directions, respectively. Conclusion: IDR can complete simulated human masticatory movement and provide sufficient biting force. Significance: The IDR provides clinical guidance for the design and performance test of artificial denture.     

智能机器人神经心理模型

为了从结构、功能和行为3个层面对智能机器人体系结构进行一体化描述,本文提出了智能机器人神经心理模型.借鉴脑的3个基本机能联合区理论建立了智能机器人的神经生理结构模型,将机器人思维系统划分为感知区、反射区和慎思区,每个区均由三级皮层构成,采用拓展的BD I逻辑(机器人心智逻辑RML)描述机器人的认知心理机制,给出了神经心理框架下的机器人智能行为过程,从理论上证明了RML的可靠性与完备性,采用水下机器人编队穿越未知雷区的对比仿真实验验证了神经心理模型的可行性和有效性.     

Four-legged intelligent mobile autonomous robot

This paper presents the design and development of a four-legged mobile robot with intelligent sensing and decision-making capabilities. Multiple sensors with embedded knowledge bases and learning capabilities are used in a novel approach towards environmental perception and reaction. These sensors continuously monitor the environment as well as their own operating parameters. Priority is given to any one or a group of sensors based on prevailing environmental conditions. Intelligent sensing is shown to be the key towards a high degree of autonomy for a mobile robot. Nicknamed Flimar, this robot has the ability to function at varying degrees of intelligence made possible by an object-oriented architecture with embedded intelligence at various levels. This architecture is shown to be conducive towards incremental learning. Each of the four legs has three degrees of freedom, i.e. Flimar has a total of 12 motors on its four legs. Flimar can walk and turn without dragging or skidding, and also turns about its center of gravity with a zero radius. Flimar responds to light, sound and touch in different ways, based on prevailing environmental conditions. The overall goal of the paper is to present a novel walking principle and control architecture for a walking robot.     

Master-slave intelligent robot telepresence system

In this paper, the analysis and design of master-slave intelligent robot telepresence system are discussed. When the operator acts on the master manipulator, the position and attitude information of the master manipulator are gathered by the computer. After calculating and coordinate transforming, the data are send to the computer of the slave manipulator. Then the slave manipulator-PUMA562 robot follows the master manipulator's movement precisely. Six-dimension force/toque sensor(lord cell) is mounted on the slave manipulator. As the master manipulator and the toque on the slave manipulator are different in structure, the force and the slave manipulator should be send to the master manipulator computer and dissociated by the master manipulator computer. Proper ratio of the force on the master manipulator and the force on the slave manipulator is selected, and distribute to the master manipulator joints. So that the operator could feel the force from the master manipulator, which is obtained by the motors of the joints. The proposed control scheme is introduced to a prototype master-slave system and the experimental results show the validity of the proposed scheme.     

鱼塘冰层智能钻孔机器人设计

本设计是以STC89C52单片机为核心,开发了一种可以通过Wi-Fi通信技术远程控制进行冰面钻孔的机器人.针对北方冬天气温低,湖面和河道会结冰,给捕鱼工作者带来困难和危险这一情况,利用51单片机和改制好的路由器进行串口通信,发送数据包来控制直流电机从而驱动机器人进行移动、钻孔的动作,再利用温度传感器进行空气温度和冰下温度的测量,所测得的数据通过Wi-Fi数据传输到主控制台,就可以得到机器人前方的实时路况.经实验检验,本设计已经能达到实现远程实时控制机器人在冰上的作业目的,降低了冰面捕鱼工作者在冰面上钻孔的危险性,并且大大提高了捕鱼效率,具有一定科研价值和应用前景.     

A mobile robot employing insect strategies for navigation

The ability to navigate in a complex environment is crucial for both animals and robots. Many animals use a combination of different strategies to return to significant locations in their environment. For example, the desert ant Cataglyphis is able to explore its desert habitat for hundreds of meters while foraging and return back to its nest precisely and on a straight line. The three main strategies that Cataglyphis is using to accomplish this task are path integration, visual piloting and systematic search. In this study, we use a synthetic methodology to gain additional insights into the navigation behavior of Cataglyphis. Inspired by the insect’s navigation system we have developed mechanisms for path integration and visual piloting that were successfully employed on the mobile robot Sahabot 2. On the one hand, the results obtained from these experiments provide support for the underlying biological models. On the other hand, by taking the parsimonious navigation strategies of insects as a guideline, computationally cheap navigation methods for mobile robots are derived from the insights gained in the experiments.     

基于图像雅可比矩阵的智能机器人视觉跟踪

根据智能机器人视觉伺服的要求,建立了固定眼结构的MOTOMAN-SV3XL型工业机器人无标定视觉伺服系统.研究了目前在机器人视觉伺服研究领域中使用最为广泛的一类方法,即基于图像雅可比矩阵的方法.针对图像雅可比矩阵的特点,设计了一种基于简化Sage-Husa自适应滤波的图像雅可比矩阵在线估计算法,并将其应用于机器人视觉反馈控制任务中,实现了对二维平面上运动目标的跟踪,实验结果表明了该算法的有效性.     

基于ARM的智能机器人语音控制应用研究

智能机器人作为机器人的研究热点,为机器人的交互提供一种方便有效的接口很重要。语音交互是一种最熟悉最自然的交互方式。在我们的个人计算机上具有丰富的软硬件资源易于语音识别技术的实现,但这也会限制了机器人的应用场合。而基于ARM的嵌入式语音识别系统可以嵌入到机器人对象内部,更适合机器人的应用需求。本文详细介绍了语音识别技术的原理,嵌入式语音识别技术的实现,机器人的语音控制技术,实验结果表明采用该方法实现机器人的语音控制可以达到方便,有效的控制效果。     

智能仿人机器人的现状及展望

仿人机器人是当前智能机器人研究领域中最新的研究方向之一,并引起了广泛的注意。本文介绍了作为智能机器人重要表现形式的仿人机器人的特点,对世界上针对仿人机器人的研究工作进行了综述,指出了各自的侧重点及不足之处,指出了今后研究工作的重点。     

Guide robot intelligent navigation in urban environments

This paper presents an intelligent robotic system to guide visually impaired people in urban environments. The robot is equipped with two laser range finders, global positioning system (GPS), camera, and compass sensors. All the sensors data are processed by a single laptop computer. We have implemented different navigation algorithms enabling the robot to move autonomously in different urban environments. In pedestrian walkways, we utilize the distance to the edge (left, right, or both) to determine the robot steering command. In difference from pedestrian walkways, in open squares where there is no edge information, artificial neural networks map the GPS and compass sensor data to robot steering command guiding the visually impaired to the goal location. The neural controller is designed such as to be employed even in environments different from those in which they have been evolved. Another important advantage is that a single neural network controls the robot to reach multiple goal locations inside the open square. The proposed algorithms are verified experimentally in a navigation task inside the University of Toyama Campus, where the robot moves from the initial to goal location.     

Caesar: an intelligent domestic service robot

In this paper we present Caesar, an intelligent domestic service robot. In domestic settings for service robots complex tasks have to be accomplished. Those tasks benefit from deliberation, from robust action execution and from flexible methods for human?Crobot interaction that account for qualitative notions used in natural language as well as human fallibility. Our robot Caesar deploys AI techniques on several levels of its system architecture. On the low-level side, system modules for localization or navigation make, for instance, use of path-planning methods, heuristic search, and Bayesian filters. For face recognition and human?Cmachine interaction, random trees and well-known methods from natural language processing are deployed. For deliberation, we use the robot programming and plan language Readylog, which was developed for the high-level control of agents and robots; it allows combining programming the behaviour using planning to find a course of action. Readylog is a variant of the robot programming language Golog. We extended Readylog to be able to cope with qualitative notions of space frequently used by humans, such as ??near?? and ??far??. This facilitates human?Crobot interaction by bridging the gap between human natural language and the numerical values needed by the robot. Further, we use Readylog to increase the flexible interpretation of human commands with decision-theoretic planning. We give an overview of the different methods deployed in Caesar and show the applicability of a system equipped with these AI techniques in domestic service robotics.     

应用形式化与实时语言的面向方面方法

面向方面的软件开发方法是在面向对象开发方法的基础上,在AOP的支持下将贯穿系统的横切关注点提取出来,通过联结方式织入系统功能代码中的软件开发方法,该方法降低了软件开发的复杂性,提高了系统的灵活性和可维护性。形式化和实时语言为面向方面方法贯穿于实时软件开发提供了必要的支持,以形式化方法AO-RT-Z和实时语言PEARL为基础,给出了一种面向方面的实时软件开发框架,实现了软件生命周期各个阶段对面向方面的无缝支持,降低了实时软件开发的复杂性,提升了系统的可信度。     

High-speed human motion recovery employing back projection

This paper describes a novel technique for high-speed human motion recovery. For 3-D human motion recovery, stereoscopic vision is a normal technique, as well as the employment of a magnetic field, but this cannot avoid the difficulty of marker tracking. In this article, a novel motion recovery technique is proposed based on the back projection of silhouette images. This technique has some advantages over others because it does not employ markers, and it has a simple architecture. In the experiment performed, the proposed motion recovery technique is implemented on a system containing a LAN, a host computer, and four pairs of camera and computer, and it achieves high-speed human motion recovery. This work was presented in part at the 10th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2005     

Web-based mobile robot platform for real-time exercises

This paper introduces a new vision-based and web-based mobile robot platform. The platform consists of control and communication centers, a mobile robot and real-time support libraries. All activities in the platform are achieved by only computer vision techniques. The platform provides monitoring, tele-controlling and programming for real-time educational exercises and helps to the users to achieve these exercises through a standard web browser without any need for additional support software. The results have shown that the proposed, designed and implemented platform provide amazing new facilities and features to the users (students and researchers) in applying their real-time exercises on web.     

Reliable people tracking approach for mobile robot in indoor environments

There is a great challenge that a mobile robot reliably and continuously tracks a specific person in indoor environments. In this paper, a novel method is presented, which can effectively recognize and reliably track a target person based on mobile robot vision. Gabor wavelet and hidden Markov model (HMM) are firstly employed for identifying the target person. In order to effectively track the specific person and reduce the computational cost in tracking stage, horizontal-projecting probability histogram (HPPH) of upper body color clothes region is proposed for extracting the pattern features, which significantly improves the tracking reliability and, at the same time, unscented particle filter (UPF) is integrated and PID operator is introduced for controlling the robot to follow the person. Experimental results validate the robustness and the reliability of this approach.     

Implementing distributed control system for intelligent mobile robot

The control system of a mobile robot has a number of issues to deal with in real time, including motion control, mapping, localization, path planning, and sensor processing. Intelligent reasoning, task-oriented behaviors, human–robot interfaces, and communications add more tasks to be solved. This naturally leads to a complex hierarchical control system where various tasks have to be processed concurrently. Many low-level tasks can be handled by a robots onboard (host) computer. However, other tasks, such as speech recognition or vision processing, are too computationally intensive for one computer to process. In this case, it is better to consider a distributed design for the control system in networked environments. In order to achieve maximum use of the distributed environment, it is important to design and implement the distributed system and its communication mechanisms in an effective and flexible way. This article describes our approach to designing and implementing a distributed control system for an intelligent mobile robot. We present our implementation of such a distributed control system for a prototype mobile robot. We focus our discussion on the system architecture, distributed communication mechanisms, and distributed robot control.This work was presented, in part, at the 8th International Symposium on Artificial Life and Robotics, Oita, Japan, January 24–26, 2003     

Mobile robot with transformable crawler and intelligent guidance

Recently, great advances have been made in intelligent mobile robot technology, advances which will provide autonomous travelling ability to robots, allowing them to surmount stairs and other obstacles. In this paper, we present an active adaptive crawler mechanism and a visual navigating system, developed to achieve practical speed for industrial use of the mobile robot. By using a crawler-type mechanism, the active adaptive suspension mechanism maintains vehicle stability and achieves good climbing capability without increasing weight. Further, we have developed technology for an intelligent navigating mechanism, to guide the robot as it passes through a building. Once the robot is provided with an inner layout plan of the respective building, it can achieve practical mobile speed for industrial use.     

Multisensor based security robot system for intelligent building

Intelligent building can provide safety, convenience, efficiency and entertainment for life in the 21st century. The most importance role of the intelligent building is the security system. We develop a multi sensor-based intelligent security robot (ISR) that is widely employed in intelligent buildings. The intelligent security robot can detect abnormal and dangerous situations and notify users. The robot has the shape of cylinder and its diameter, height, and weight are 50 cm, 130 cm and 100 kg respectively. The function of the ISR contains six parts. There is the software development system; avoiding obstacle and motion planning system, image system, sensor system, remote supervise system and other systems. We develop a multi sensor-based sensor system in the ISR. We use multiple multisensor fusion algorithms to get an exact decision in the detection subsystem of the sensor system. There is an adaptive fusion method, a rule based method, and a statistical signal method. We demonstrate the remote supervisory system to control the ISR using a direct control mode and a behavior control mode. We think that the man–machine interface in a security robot system must have mobility and convenience. Therefore, we use a touch screen to display the system state, and design a general user interface (GUI) to service the user and visitors. The user can remotely control the appliance using a cell phone through a GSM modem, too. The appliance module can feedback reaction results to the user through a cell phone. Finally, we implement the fire detection system in the intelligent security robot (Chung-Cheng-I). If a fire occurs, the intelligent security robot can find out the fire source using the fire detection system. In intruder detection, we program the same scenario to detect the intruder using the intelligent security robot. The intelligent security robot transmits the message of the detection result to the user using a GSM modem for a fire event or intruder, and transmits the detection result to a client computer through the internet.     

Robust robot knowledge instantiation for intelligent service robots

Robot knowledge is considered to endow service robots with intelligence. In the real environments, robot knowledge needs to represent dynamically changing world. Despite its advantages for semantic knowledge of service robots, robot knowledge may be instantiated and updated by using imperfect sensing data, such as misidentification of object recognition. In case of using commercially available visual recognition system, incorrect knowledge instances are created and changed frequently due to object misidentification and/or recognition failures. In this work, a robust semantic knowledge handling method under imperfect object recognition is proposed to instantiate and update robot knowledge with logical inference by estimating confidence of the object recognition results. The following properties may be applied to determine misidentifications in logical inference: temporal reasoning to represent relationships between time intervals, statistical reasoning with confidence of object recognition results. To show validity of our proposed method, experimental results are illustrated, where commercial visual recognition system is employed.