Incorporation of acoustic sensors in the regulation of a mobile robot

This article introduces the incorporation of acoustic sensors for the localization of a mobile robot. The robot is considered as a sound source and its position is located applying a Time Delay of Arrival (TDOA) method. Since the accuracy of this method varies with the microphone array, a navigation acoustic map that indicates the location errors is built. This map also provides the robot with navigation trajectories point-to-point and the control is capable to drive the robot through these trajectories to a desired configuration. The proposed localization method is thoroughly tested using both a 900?Hz square signal and the natural sound of the robot, which is driven near the desired point with an average error of 0.067?m.     

Nonlinear filtering in target tracking using cooperative mobile sensors

Collaborative signal processing and sensor deployment have been among the most important research tasks in target tracking using networked sensors. In this paper, the mathematical model is formulated for single target tracking using mobile nonlinear scalar range sensors. Then a sensor deployment strategy is proposed for the mobile sensors and a nonlinear convergent filter is built to estimate the trajectory of the target.     

Estimation and control of the attitude of a dynamic mobile robot using internal sensors

For the control of a dynamic mobile robot, the attitude in gravity space is an important state of the robot. Usually, the attitude is difficult to detect by simply using the signals from sensors. For example, an external sensor contacting the ground suffers disturbances from the roughness of the ground; the integration of a gyroscope signal has the problem of drift; an inclination sensor does not indicate the direction of gravity when acceleration exists. To solve these problems, we propose a control method in which the attitude of a mobile robot is estimated by an observer considering the robot dynamics and using only the information obtained by internal sensors. We applied this method to a wheeled inverted pendulum as an example of a dynamic mobile robot. The estimation of the attitude was made with good accuracy using the signals from the rate gyroscope and the motor encoder, and the control of stable running of the pendulum on a flat level plane worked successfully. We also realized the running control of a pendulum on an unknown rough road using the estimation of the slope gradient made by the observer. Thus, the effectiveness of the proposed method was demonstrated experimentally.     

Distributed information-based guidance of multiple mobile sensors for urban target search

We present a framework for distributed mobile sensor guidance to locate and track a target inside an urban environment. Our approach leverages the communications between robots when a link is available, but it also allows them to act independently. Each robot actively seeks the target using information maximization. The robots are assumed to be capable of communicating with their peers within some distance radius, and the sensor payload of each robot is a camera modeled to have target detection errors of types I and II. Our contributions include an optimal information fusion algorithm for discrete distributions which allows each agent to combine its local information with that of its neighbors, and a path planner that uses the fused estimate and a recent coverage result for information maximization to guide the agents. We include simulations and laboratory experiments involving multiple robots searching for a moving target within model cities of different sizes.     

Positioning device for outdoor mobile robots using optical sensors and lasers

We propose a novel method for positioning a mobile robot in an outdoor environment using lasers and optical sensors. Position estimation via a noncontact optical method is useful because the information from the wheel odometer and the global positioning system in a mobile robot is unreliable in some situations. Contact optical sensors such as computer mouse are designed to be in contact with a surface and do not function well in strong ambient light conditions. To mitigate the challenges of an outdoor environment, we developed an optical device with a bandpass filter and a pipe to restrict solar light and to detect translation. The use of two devices enables sensing of the mobile robot’s position, including posture. Furthermore, employing a collimated laser beam allows measurements against a surface to be invariable with the distance to the surface. In this paper, we describe motion estimation, device configurations, and several tests for performance evaluation. We also present the experimental positioning results from a vehicle equipped with our optical device on an outdoor path. Finally, we discuss an improvement in postural accuracy by combining an optical device with precise gyroscopes.     

基于光流传感器的移动机器人定位方法

详细介绍了光流传感器移动机器人定位系统的运动学原理,给出了理论模型推导;基于理论模型,搭建了基于光流传感器实验装置,将3只传感器置于移动机器人的固定位置,通过运动学几何关系,解算机器人的位姿;在室内进行了移动机器人的导航实验,推算了机器人的预测轨迹.实验证明了理论的可行性,可以作为短距离定位的一种导航方案.     

Fuzzy target tracking control of autonomous mobile robots by using infrared sensors

The theme of this paper is to design a real-time fuzzy target tracking control scheme for autonomous mobile robots by using infrared sensors. At first two mobile robots are setup in the target tracking problem, where one is the target mobile robot with infrared transmitters and the other one is the tracker mobile robot with infrared receivers and reflective sensors. The former is designed to drive in a specific trajectory. The latter is designed to track the target mobile robot. Then we address the design of the fuzzy target tracking control unit, which consists of a behavior network and a gate network. The behavior network possesses the fuzzy wall following control (FWFC) mode, fuzzy target tracking control (FTTC) mode, and two fixed control modes to deal with different situations in real applications. Both the FWFC and FTTC are realized by the fuzzy sliding-mode control scheme. A gate network is used to address the fusion of measurements of two infrared sensors and is developed to recognize which situation is belonged to and which action should be executed. Moreover, the target tracking control with obstacle avoidance is also investigated in this paper. Both computer simulations and real-time implementation experiments of autonomous target tracking control demonstrate the effectiveness and feasibility of the proposed control schemes.     

Self-deployment of mobile sensors on a ring

Mobile sensors can self-deploy in a purely decentralized and distributed fashion, so as to reach in a finite time a state of static equilibrium in which they uniformly cover the environment. We consider the self-deployment problem in a ring (e.g., a circular rim); in particular we investigate under what conditions the problem is solvable by a collection of identical sensors without a global coordinate system, however capable of determining the location (in their local coordinate system) of the other sensors within a fixed distance (called visibility radius). A self-deployment is exact   if within finite time the distance between any two consecutive sensors along the ring is the same, d$d$; it is ?$?$-approximate   if within finite time the distance between two consecutive sensors is between d−?$d-?$ and d+?$d+?$.     

Position estimation of a mobile robot using images of a moving target in intelligent space with distributed sensors

Latest advances in hardware technology and state-of-the-art of mobile robots and artificial intelligence research can be employed to develop autonomous and distributed monitoring systems. A mobile service robot requires the perception of its present position to co-exist with humans and support humans effectively in populated environments. To realize this, a robot needs to keep track of relevant changes in the environment. This paper proposes localization of a mobile robot using images recognized by distributed intelligent networked devices in intelligent space (ISpace) in order to achieve these goals. This scheme combines data from the observed position, using dead-reckoning sensors, and the estimated position, using images of moving objects, such as a walking human captured by a camera system, to determine the location of a mobile robot. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the ISpace. Using the a priori known path of a moving object and a perspective camera model, the geometric constraint equations that represent the relation between image frame coordinates for a moving object and the estimated robot's position are derived. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot, and the Kalman filtering scheme is used for the estimation of the mobile robot location. The proposed approach is applied for a mobile robot in ISpace to show the reduction of uncertainty in determining the location of a mobile robot, and its performance is verified by computer simulation and experiment.     

Trajectroy prediction for target tracking using acoustic and image hybrid wireless multimedia sensors networks

Wireless multimedia sensor networks (WMSN), with self-organizing and high fault tolerant characteristics, have achieved great advantages in target tracking region. However, the capabilities of these tiny devices are limited by their battery power, storage capacity, computational ability and communication bandwidth. In this paper, hybrid wireless multimedia sensors networks composed of acoustic and image sensors are proposed for target tracking. When the target appears in the detection area, it may change the environment parameters nearby, so acoustic sensors are used to gather target signal firstly. Then, a target location method is executed based on the strength of the received acoustic signal. Furthermore, to achieve energy-efficient target tracking with high reliability and robust, image sensors are used as supplements to the acoustic sensors. This approach also reduces the power consumption communication burden of the whole networks. In order to decrease the number of active nodes, Gauss Markov mobility model is also adopted to predict the target trajectory and minimize the tracking region with considering of vehicular kinematics. Simulation results verify that, compared with other algorithms, our scheme can reduce the energy consumption and improve tracking accuracy.     

Patrolling a barrier with a network of mobile sensors

Comparative analysis of the efficiency of two organizational patterns of networks consisting of mobile sensors and designed for patrolling a barrier in the case when the sensor detection range depends on the objects’ velocities is performed.     

Dynamic target tracking and observing in a mobile sensor network

This paper presents novel approaches to (1) the problem of flocking control of a mobile sensor network to track and observe a moving target and (2) the problem of sensor splitting/merging to track and observe multiple targets in a dynamic fashion. First, to deal with complex environments when the mobile sensor network has to pass through a narrow space among obstacles, we propose an adaptive flocking control algorithm in which each sensor can cooperatively learn the network’s parameters to decide the network size in a decentralized fashion so that the connectivity, tracking performance and formation can be improved. Second, for multiple dynamic target tracking, a seed growing graph partition (SGGP) algorithm is proposed to solve the splitting/merging problem. To validate the adaptive flocking control we tested it and compared it with the regular flocking control algorithm. For multiple dynamic target tracking, to demonstrate the benefit of the SGGP algorithm in terms of total energy and time consumption when sensors split, we compared it with the random selection (RS) algorithm. Several experimental tests validate our theoretical results.     

Environmental map building for a mobile robot using infrared range-finder sensors

This paper presents a methodology for building a high-accuracy environmental map using a mobile robot. The design approach uses low-cost infrared range-finder sensors incorporating with neural networks. To enhance the map quality, the errors occurring from the sensors are corrected. The non-linearity error of the sensors is compensated using a backpropagation neural network and the random error of readings including the uncertainty of the environment is taken into a sensor model as a probabilistic approach. The map is represented by an occupancy grid framework and updated by the Bayesian estimation mechanism. The effectiveness of the proposed method is verified through a series of experiments.     

VISYR: a simulation tool for mobile robots using vision sensors

With the advent of mobile robots and inboard vision sensors mounted directly on the robot's wrist, new kinds of problems lie in the image processing field as, for example, dynamic scene analysis or motion estimation. The lack of flexibility of real experiments led us to implement at IRISA a general simulation tool devoted to the study of robots using moving vision sensors. VISYR allows us to simulate the image perceived by a robot of its environment during its motion.The first part of the paper is devoted to the modelling of the 3D scene containing complex objects and to the design of a suitable robotics vision sensor. In the second part, a new algorithm of dynamic management of the local data basis perceived by the sensor is presented. The parameters of the vision sensors are highly adjustable and VISYR is conceived to allow the fast development of algorithms using dynamic vision data.     

纯方位角目标跟踪及移动平台可观性控制方法

为了解决未知环境下的单目视觉移动机器人目标跟踪问题,提出了一种将目标状态估计与机器人可观性控制相结合的机器人同时定位、地图构建与目标跟踪方法。在状态估计方面,以机器人单目视觉同时定位与地图构建为基础,设计了扩展式卡尔曼滤波框架下的目标跟踪算法;在机器人可观性控制方面,设计了基于目标协方差阵更新最大化的优化控制方法。该方法能够实现机器人在单目视觉条件下对自身状态、环境状态、目标状态的同步估计以及目标跟随。仿真和原型样机实验验证了目标状态估计和机器人控制之间的耦合关系,证明了方法的准确性和有效性,结果表明:机器人将产生螺旋状机动运动轨迹,同时,目标跟踪和机器人定位精度与机器人机动能力成正比例关系。     

Optimal movement of mobile sensors for barrier coverage of a planar region

Intrusion detection, area coverage and border surveillance are important applications of wireless sensor networks today. They can be (and are being) used to monitor large unprotected areas so as to detect intruders as they cross a border or as they penetrate a protected area. We consider the problem of how to optimally move mobile sensors to the fence (perimeter) of a region delimited by a simple polygon in order to detect intruders from either entering its interior or exiting from it. We discuss several related issues and problems, propose two models, provide algorithms and analyze their optimal mobility behavior.     

Switched visual servo control of nonholonomic mobile robots with field-of-view constraints based on homography

This paper presents a novel scheme for visual servoing of a nonholonomic mobile robot equipped with a monocular camera in consideration of field-of-view (FOV) constraints. In order to loosen the FOV constraints, the system states are expressed by the homography between the current frame and the key frame so that the target is not necessarily to be always visible in the control process. A switched visual controller is designed to deal with the nonholonomic constraints. Moreover, an iteration strategy is used to eliminate errors caused by the parameter uncertainty. The stablity and robustness of the proposed scheme are guaranteed by theoretical analysis. Compared to conventional schemes, the proposed approach has the following advantages: 1) a better path in Cartesian space can be achieved owing to the loosening of FOV constraints; 2) the iteration strategy ensures the robustness to parameter uncertainty; 3) when used in landmark-based navigation, it needs much sparser and simpler landmarks than those localization-based approaches need. Simulation results demonstrate the effectiveness of the proposed method.     

光化学氧传感器技术的研究进展

综述了近年来国内外光化学氧传感器技术的研究及应用情况,简要介绍了光化学氧传感器的原理及响应机理,详细讨论了荧光敏感物质和支持体系的进展,并展望了光化学氧传感器的发展趋势.     

Vision-based interception of a moving target with a nonholonomic mobile robot

A novel vision-based scheme is presented for driving a nonholonomic mobile robot to intercept a moving target. The proposed method has a two-level structure. On the lower level, the pan–tilt platform carrying the on-board camera is controlled so as to keep the target as close as possible to the center of the image plane. On the higher level, the relative position of the target is retrieved from its image coordinates and the camera pan–tilt angles through simple geometry, and used to compute a control law which drives the robot to the target. Various possible choices are discussed for the high-level robot controller, and the associated stability properties are rigorously analysed. The proposed visual interception method is validated through simulations as well as experiments on the mobile robot MagellanPro.     

Computation in networks of passively mobile finite-state sensors

The computational power of networks of small resource-limited mobile agents is explored. Two new models of computation based on pairwise interactions of finite-state agents in populations of finite but unbounded size are defined. With a fairness condition on interactions, the concept of stable computation of a function or predicate is defined. Protocols are given that stably compute any predicate in the class definable by formulas of Presburger arithmetic, which includes Boolean combinations of threshold-k, majority, and equivalence modulo m. All stably computable predicates are shown to be in NL. Assuming uniform random sampling of interacting pairs yields the model of conjugating automata. Any counter machine with O(1) counters of capacity O(n) can be simulated with high probability by a conjugating automaton in a population of size n. All predicates computable with high probability in this model are shown to be in P; they can also be computed by a randomized logspace machine in exponential time. Several open problems and promising future directions are discussed. Supported in part by NSF grants CCR-9820888, CCR-0098078, and CNS-0305258 (Aspnes), by ONR grant N00014-01-1-0795 (Diamadi), and by NSF grant CSE-0081823 (Fischer and Peralta). A preliminary version of this paper appeared in the proceedings of the 23rd ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing, St. John’s, Newfoundland, Canada, July 2004.