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Integration of camera and range sensors for 3D pose estimation in robot visual servoing

Integration of camera and range sensors for 3D pose estimati...

引用

Conference on sensor fusion amd decentralized control in robotic systems

作者： Hulls, CCW Wilson, WJ Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada

ISBN: (纸本)0819429848

Range-vision sensor systems can incorporate range images or single point measurements. Research incorporating point range measurements has focused on the area of map generation for mobile robots. These systems can utilize the fact that the objects sensed tend to be large and planar. The approach presented in this paper fuses information obtained from a point range measurement with visual information to produce estimates of the relative 3D position and orientation of a small, non-planar object with respect to a robot end-effector. The paper describes a real-time sensor fusion system for performing dynamic visual servoing using a camera and a point laser range sensor. The system is based upon the object model reference approach. This approach, which can be used to develop multi-sensor fusion systems that fuse dynamic sensor data from diverse sensors in real-time, uses a description of the object to be sensed in order to develop a combined observation-dependency sensor model. The range-vision sensor system is evaluated in terms of accuracy and robustness. The results show that the use of a range sensor significantly improves the system performance when there is poor or insufficient camera information. The system developed is suitable for visual servoing applications, particularly robot assembly operations.

关键词： sensor fusion vision pose estimation robot control

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sensor-fused navigation and manipulation from a planetary rover

Sensor-fused navigation and manipulation from a planetary ro...

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Conference on sensor fusion amd decentralized control in robotic systems

作者： Baumgartner, ET Leger, PC Schenker, PS Huntsberger, TL CALTECH Jet Prop Lab Sci & Technol Dev Sect Pasadena CA 91109 USA

ISBN: (纸本)0819429848

This paper describes the development of advanced rover navigation and manipulation techniques for use by NASA's Sample Return Rover. These techniques include an algorithm for estimating the change in the rover's position aid orientation ky registering successive range maps from the rover's hazard avoidance stereo camera pair and the fusion of this information with the rover's wheel odometry. This map registration technique is also extended to register range maps to an a priori model-based range map for relative rover position and orientation determination. Finally, a technique for the robust and precise positioning of a rover-mounted manipulator using visual feedback from the rover's stereo pair is presented. Experimental results for each of these techniques is documented in this paper.

关键词： rover navigation state estimation map registration vision-based manipulation

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sensor supervision and multi-agent commanding by means of "Projective Virtual Reality"

Sensor supervision and multi-agent commanding by means of "P...

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Conference on sensor fusion amd decentralized control in robotic systems

作者： Rossmann, J Univ Dortmund Inst Robot Res D-44227 Dortmund Germany

ISBN: (纸本)0819429848

When autonomous systems with multiple agents are considered, conventional control- and supervision technologies are often inadequate because the amount of information available is often presented in a way that the user is effectively overwhelmed by the displayed data. New virtual reality (VR) techniques can help to cope with this problem, because VR offers the chance to convey information in a intuitive manner and can combine supervision capabilities and new, intuitive approaches to the control of autonomous systems. In the approach taken, control and supervision issues were equally stressed and finally led to the new ideas and the general framework for Projective Virtual Reality. The key idea of this new approach for an intuitively operable man machine interface for decentrally controlled multi-agent systems is to let the user act in the virtual world, detect the changes and have an action planning component automatically generate task descriptions for the agents involved to project actions that have been carried out by users in the virtual world into the physical world, e.g. with the help of robots. Thus the Projective Virtual Reality approach is to split the job between the task deduction in the VR and the task "projection" onto the physical automation components by the automatic action planning component. Besides describing the realized projective virtual reality system, the paper will also describe in detail the metaphors and visualization aids used to present different types of (e.g. sensor-) information in an intuitively comprehensible manner.

关键词： Virtual reality Robots control systems sensors Visualization Space robots Cameras robotic systems Computer simulations robotics

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Dynamic sensor action selection with Bayesian decision analysis

Dynamic sensor action selection with Bayesian decision analy...

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Conference on sensor fusion amd decentralized control in robotic systems

作者： Kristensen, S Hansen, V Kondak, K Daimler Benz AG Res Lab Autonomous Syst Intelligent Syst Grp D-10559 Berlin Germany

ISBN: (纸本)0819429848

The aim of this work is to create a framework for the dynamic planning of sensor actions for an autonomous mobile robot. The framework uses Bayesian decision analysis, i.e., a decision-theoretic method, to evaluate possible sensor actions and selecting the most appropriate ones given the available sensors and what is currently known about the state of the world. Since sensing changes the knowledge of the system and since the current state of the robot (task, position, etc.) determines what knowledge is relevant, the evaluation and selection of sensing actions is an on-going process that effectively determines the behaviour of the robot. The framework has been implemented on a real mobile robot and has been proven to be able to central in real-time the sensor actions of the system. In current work we are investigating methods to reduce or automatically generate the necessary model information needed by the decision-theoretic method to select the appropriate sensor actions.

关键词： sensor selection action selection Bayesian decision analysis mobile robots

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A framework for implementing self-organising task-oriented multi-sensor networks

A framework for implementing self-organising task-oriented m...

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Conference on sensor fusion amd decentralized control in robotic systems

作者： Scheering, C Knoll, A Univ Bielefeld Fac Technol D-33501 Bielefeld Germany

ISBN: (纸本)0819429848

Advanced manipulation skills that enable cooperating robots in a work cell to recognise, handle and assemble arbitrarily placed objects require sensory information on both the environment and assembly process. Using standard approaches it becomes difficult to coordinate sensor usage and data fusion under a given task when the number of sensors becomes large or is changed during run-time. We present a solution to both coordination and fusion based on the multi (sensor) agent paradigm: each agent implements a sensory skill, a negotiation protocol and a physical communication interface to all other agents. Within this sensor-network teams cooperate on a common task. They are formed dynamically after a negotiation phase following a specific task formulation. Our framework consists of a formal specification of the requirements that the sensory skill of an agent has to meet and a comprehensive library of (C++)-objects encapsulating all of the negotiation protocol and communications. This separation makes it very easy to implement individual sensory skills. We show how the abstract concepts of this approach and the metaphor of "negotiation" work in a real-world network: several uncalibrated cameras are used to guide a manipulator towards a target. We also show how agent-teams may easily (self-)reconfigure during task execution in the case of unexpected events. The framework is distributed free of charge and can be obtained over the Internet at http://***.

关键词： multi-sensor network distributed sensing sensor-fusion multi-agents uncalibrated visual servoing contract net

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Nonholonomic camera space manipulation using cameras mounted on a mobile base

Nonholonomic camera space manipulation using cameras mounted...

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Conference on sensor fusion amd decentralized control in robotic systems

作者： Goodwine, B Seelinger, M Skaar, SB Ma, Q Univ Notre Dame Notre Dame IN 46556 USA

ISBN: (纸本)0819429848

The body of work called "Camera Space Manipulation" is an effective and proven method of robotic control. Essentially, this technique identifies and refines the input-output relationship of the plant using estimation methods and drives the plant open-loop to its target state. Three-dimensional "success" of the desired motion, i.e., the end effector of the manipulator engages a target at a particular location with a particular orientation, is guaranteed when theres is camera space success in two cameras which are adequately separated. Very accurate, sub-pixel positioning of a robotic end effector is possible using this method. To date, however, most efforts in this area have primarily considered holonomic systems. This work addresses the problem of nonholonomic camera space manipulation by considering the problem of a nonholonomic robot with two cameras and a holonomic manipulator on board the nonholonomic platform. While perhaps not as common in robotics, such a combination of holonomic and nonholonomic degrees of freedom are ubiquitous in industry: fork lifts and earth moving equipment are common examples of a nonholonomic system with an on-board holonomic actuator. The nonholonomic nature of the system makes the automation problem more difficult due to a variety of reasons;in particular, the target location is not fixed in the image planes, as it is for holonomic systems (since the cameras are attached to a moving platform), and there is a fundamental "path dependent" nature of nonholonomic kinematics. This work focuses on the sensor space or camera-space-based control laws necessary for effectively implementing an autonomous system of this type.

关键词： camera space manipulation robotic vision

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Fault tolerant action selection for planetary rover control

Fault tolerant action selection for planetary rover control

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Conference on sensor fusion amd decentralized control in robotic systems

作者： Huntsberger, T Univ S Carolina Dept Comp Sci Intelligent Syst Lab Columbia SC 29208 USA

ISBN: (纸本)0819429848

The ability of a small rover to operate semi-autonomously in a hazardous planetary environment was recently demonstrated by the Sojourner mission to Mars in July of 1997. Sojourner stayed within a 50 meter radius of the Pathfinder lander. Current NASA plans call for extended year-long multikilometer treks for the 2003 and 2005 missions. A greater deal of rover autonomy is required for such missions. We have recently developed a hybrid wavelet/neural network based system called BISMARC (Biologically Inspired System for Map-based Autonomous Rover control), that is capable of such autonomy. Simulations reported at this meeting last year demonstrated that the system is capable of control for multiple rovers involved in a multiple cache recovery scenario. This robust behavior was obtained through the use of a free-flow hierarchy (FFH) as an action selection mechanism. This paper extends BISMARC to include fault tolerance in the sensing and mechanic rover subsystems. The results of simulation studies in a Mars environment are also reported.

关键词： autonomous rovers behavior-based control fault tolerance control hierarchies

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Data fusion for 3D object reconstruction

Data fusion for 3D object reconstruction

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Conference on sensor fusion amd decentralized control in robotic systems

作者： Mostafa, MGH Yamany, SM Farag, AA Univ Louisville EE Dept Comp Vis & Image Proc Lab Louisville KY 40292 USA

ISBN: (纸本)0819429848

Recently multisensor data fusion has proven its necessity for computer vision and robotics applications. Three-dimensional (3D) scene reconstruction and model building have been greatly improved in systems that employ multiple sensors and/or multiple cues data fusion/integration. In this paper, we present a framework for integrating registered multiple sensory data, sparse range data from laser range finders and dense depth maps of shape from shading from intensity images, for improving the 3D reconstruction of visible surfaces of 3D objects. Two methods are used for data integration and surface reconstruction. In the first method, data are integrated using a local error propagation algorithm, which we have developed in this paper. In the second method, the integration process is carried out using a feedforward neural networks with backpropagation learning rule. It is found that the integration of sparse depth measurements has greatly enhanced the 3D visible surface obtained from shape from shading in terms of metric measurements. We also review the current research in the area of multisensor/multicue data fusion for 3D object reconstructions.

关键词： data fusion computer vision surface reconstruction surface interpolations shape from shading neural networks

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Self-development of visual space perception by learning from the hand

Self-development of visual space perception by learning from...

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Conference on sensor fusion amd decentralized control in robotic systems

作者： Chung, JM Ohnishi, N RIKEN Inst Phys & Chem Res Biomimet Control Res Ctr Moriyama Ku Nagoya Aichi 463 Japan

ISBN: (纸本)0819429848

Animals have been considered to develope ability for interpreting images captured on their retina by themselves gradually from their birth. For this they do not need external supervisor. We think that the visual function is obtained together with the development of hand reaching and grasping operations which are executed by active interaction with environment. On the viewpoint of hand teaches eye, this paper shows how visual space perception is developed in a simulated robot. The robot has simplified human-like structure used for hand-eye coordination. From the experimental results it may be possible to validate the method to describe how visual space perception of biological systems is developed. In addition the description gives a way to self-calibrate the vision of intelligent robot based on learn by doing manner without external supervision.

关键词： self-developing robot visual space perception absolute size perception size constancy stereo eye motion learning from the hand reaching grasping

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Decision and feature fusion over the fractal inference network using camera and range sensors

Decision and feature fusion over the fractal inference netwo...

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Conference on sensor fusion amd decentralized control in robotic systems

作者： Erkmen, I Erkmen, AM Ucar, E Middle E Tech Univ Dept Elect & Elect Engn TR-06531 Ankara Turkey

ISBN: (纸本)0819429848

The objective of the ongoing work is to fuse information from uncertain environmental data taken by cameras, short range sensors including infrared and ultrasound sensors for strategic target recognition and task specific action in Mobile Robot applications. Our present goal in this paper is to demonstrate target recognition for service robot in a simple office environment. It is proposed to fuse all sensory signals obtained from multiple sensors over a fully layer-connected sensor network system that provides an equal opportunity competitive environment for sensory data where those bearing less uncertainty, less complexity and less inconsistencies with the overall goal survive, while others fade out. In our work, this task is achieved as a decision fusion using the Fractal Inference Network (FIN), where information patterns or units- modelled as textured belief functions bearing a fractal dimension due to uncertainty - propagate while being processed at the nodes of the network. Each local process of a node generates a multiresolutional feature fusion. In this model, the environment is observed by multisensors of different type, different resolution and different spatial location without a prescheduled sensing scenario in data gathering. Node activation and flow control of information over the FIN is performed by a neuro-controller, a concept that has been developed recently as an improvement over the classical Fractal Inference Network. In this paper, the mathematical closed form representation for decision fusion over the FIN is developed in a way suitable for analysis and is applied to a NOMAD mobile robot servicing an office environment.

关键词： fractal inference network multiresolutional sensor fusion belief functions evidential logical sensors textured belief networks

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