intelligent space (iSpace) is a large scale mechatronics system. It is a multidisciplinary effort whose aim is to produce a network structure and components that are capable of integrating sensors, actuators, DSP, com...
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intelligent space (iSpace) is a large scale mechatronics system. It is a multidisciplinary effort whose aim is to produce a network structure and components that are capable of integrating sensors, actuators, DSP, communication, and control algorithms in a manner that suits time-sensitive applications including real-time navigation and/or obstacle avoidance. There are many challenges that must be overcome in order to put such a distributed, heterogeneous system together. This paper deals with one of these issues, i.e. the adverse effect of network and processing delays on the system. Here a delay-resistant sensory motor module for navigating a differential drive unmanned ground vehicle (UGV) in a cluttered environment is suggested. The module consists of an early vision edge detection stage, a harmonic potential field (HPF) planner, a network based quadratic curve fitting controller and gain schedule middleware, (GSM). Though the different techniques used to implement the navigation system have been well-studied as independent modules, the contribution in this paper is the way all these different modules are integrated together for the first time to create an efficient structure for a network based integrated navigation system. The structure of this module and its components are described. Thorough experimental results along with performance assessment comparing the suggested structure to a previous implementation of iSpace are also provided
This paper presents an extension of the binocular technique which considers reciprocal reflectance of surfaces. This particular property allows to recover depth information for surfaces where others stereo techniques ...
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This paper presents an extension of the binocular technique which considers reciprocal reflectance of surfaces. This particular property allows to recover depth information for surfaces where others stereo techniques failed, for example, textureless and highly specular surfaces. The consideration of an arbitrary BRDF (Bidirectional Reflectance Distribution Function) improves conventional stereo algorithms, in such a way that explicit or implicit assumptions about a reflectance function are not necessary and dense depth maps are obtained. Fixed specularities and correspondence between half-occluded regions reduce processing complexity which is an important advantage of this methodology. This paper provides a general geometry assembly to this approach extending its applicability to some specific areas where accurate depth measures are required. Several results from our implementation are shown using rendered ray-tracing stereo images.
The proceedings contain 38 papers from the Proceedings of SPIE: intelligentrobots and computervision XXII: algorithms, techniques, and Active vision. The topics discussed include: advances in learning for intelligen...
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The proceedings contain 38 papers from the Proceedings of SPIE: intelligentrobots and computervision XXII: algorithms, techniques, and Active vision. The topics discussed include: advances in learning for intelligent mobile robots;advanced remote operation of swarms of robots;a method for integrating vision and laser range measurements in autonomous ground robotic vehicles;calculation of the shortest-time path for traversal of an obstacle course by a robot;autonomous robot vision software design using Matlab toolboxes;visual terrain mapping for traversable path planning of mobile robots;segmentation algorithm for objects with very low edge contrast;and Bayesian stereo: 3D vision designed for sensor fusion.
A new navigation method is described for an indoor mobile robot. The robot system is composed of a Radio Frequency Identification (RFID) tag sensor and a commercial three-wheel mobile platform with ultrasonic rangefin...
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ISBN:
(纸本)0819460303
A new navigation method is described for an indoor mobile robot. The robot system is composed of a Radio Frequency Identification (RFID) tag sensor and a commercial three-wheel mobile platform with ultrasonic rangefinders. The RFID tags are used as landmarks for navigation and the topological relation map which shows the connection of scattered tags through the environment is used as course instructions to a goal. The robot automatically follows paths using the ultrasonic rangefinders until a tag is found and then refers the next movement to the topological map for a decision. Our proposed technique would be useful for real-world robotic applications such as intelligent navigation for motorized wheelchairs.
Spherical robot, rolling by altering its' barycenter with the inside actuating device, has a spherical or spheroid housing, the motivity of which is supplied by the friction force between the housing and the groun...
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Spherical robot, rolling by altering its' barycenter with the inside actuating device, has a spherical or spheroid housing, the motivity of which is supplied by the friction force between the housing and the ground while it rolling. Particular attention is paid to the research of spherical robot in recent years. This paper presents a new omnidirectional bi-driver spherical robot droved by two motors that directly drive the balancer to rotate about two orthogonal axes. The spherical robot is a nonholonomic system with 3 DOF while it rolls on the ground, so the spherical presented in this paper is a nonholonomic under-actuated system, featuring omnidirectional movement, simple configuration, and so on.
The purpose of this paper is to describe the concept and architecture for an intelligent robot system that can adapt, learn and predict the future. This evolutionary approach to the design of intelligentrobots is the...
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The purpose of this paper is to describe the concept and architecture for an intelligent robot system that can adapt, learn and predict the future. This evolutionary approach to the design of intelligentrobots is the result of several years of study on the design of intelligent machines that could adapt using computervision or other sensory inputs, learn using artificial neural networks or genetic algorithms, exhibit semiotic closure with a creative controller and perceive present situations by interpretation of visual and voice commands. This information processing would then permit the robot to predict the future and plan its actions accordingly. In this paper we show that the capability to adapt, and learn naturally leads to the ability to predict the future state of the environment which is just another form of semiotic closure. That is, predicting a future state without knowledge of the future is similar to making a present action without knowledge of the present state. The theory will be illustrated by considering the situation of guiding a mobile robot through an unstructured environment for a rescue operation. The significance of this work is in providing a greater understanding of the applications of learning to mobile robots.
A goal of robotics has been to develop mechanisms that have the efficiency and speed of wheeled robots with the terrain flexibility of legged robots. In previous work, we have proposed a unique three-legged mechanism,...
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A goal of robotics has been to develop mechanisms that have the efficiency and speed of wheeled robots with the terrain flexibility of legged robots. In previous work, we have proposed a unique three-legged mechanism, the rotopod, designed to integrate these two useful approaches to locomotion. In this paper, we present an analysis of the variety of gaits that can be exhibited by the rotopod. We present examples of many of these gaits and discuss their potential use. A trajectory generation algorithm is presented that can be used to generate point to point trajectories using one of three different styles of gait.
intelligent tactical behaviors of robots and UGVs cannot be achieved without a perception system that is similar to human vision. The traditional linear bottom-up "segmentation-grouping-learning-recognition"...
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intelligent tactical behaviors of robots and UGVs cannot be achieved without a perception system that is similar to human vision. The traditional linear bottom-up "segmentation-grouping-learning-recognition" approach to image processing and analysis cannot provide a reliable separation of an object from its background or clutter, while human vision unambiguously solves this problem. The nature of informational processes in the visual system does not allow separating from the informational processes in the top-level knowledge system. An Image/Video Analysis that is based on Network-Symbolic approach is a combination of recursive hierarchical bottom-up and top-down processes. Instead of precise computations of 3-dimensional models a Network-Symbolic system converts image information into an "understandable" Network-Symbolic format that is similar to the relational knowledge models. The logic of visual scenes can be captured in the Network-Symbolic models and used for the reliable disambiguation of visual information, including object detection and identification. View-based object recognition is a hard problem for traditional algorithms that directly match a primary view of an object to a model. In Network-Symbolic Models, the derived structure and not the primary view is a subject for recognition. Such recognition is not affected by local changes and appearances of the object from a set of similar views, and a robot can better interpret images and video for intelligent tactical behavior.
This paper presents the development and testing of a sensor payload for use on unmanned helicopters. This payload is designed to be used to detect and geo-position unexploded ordnance termed UXOs. This technology will...
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This paper presents the development and testing of a sensor payload for use on unmanned helicopters. This payload is designed to be used to detect and geo-position unexploded ordnance termed UXOs. This technology will be beneficial to explosive ordnance disposal personnel in their test range clearance operations. This payload is capable of gathering image, attitude, and position information during flight, and a suite of software programs was developed capable of modeling, classifying, and geo-positioning UXOs.
In comparison to other mobile robots, spherical rolling robots offer greater mobility, stability, and scope for operation in hazardous environments. Spherical rolling robots have been attracting much attention in not ...
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In comparison to other mobile robots, spherical rolling robots offer greater mobility, stability, and scope for operation in hazardous environments. Spherical rolling robots have been attracting much attention in not only mechanical but also control literature recently, due to both their relevance to practical applications, and to the difficulties in the analysis and control of these robots. The positioning of a spherical rolling robot at an arbitrary pose and at any time is one of the fundamental and difficult problems in the research of spherical rolling robots. Because spherical rolling robot touches the floor at a point, the positioning is difficult, especially when it moves at a high speed. Up to now, this problem has not been solved perfectly. In this paper, we present an efficient positioning approach for a spherical rolling robot. Based on the approach, a moving spherical rolling robot can be positioned at an arbitrary pose and at any time.
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