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Goal tracking in a natural language interface: towards achieving adjustable autonomy

Goal tracking in a natural language interface: towards achie...

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ieee international symposium on computational intelligence in robotics and automation (CIRA)

作者： D. Perzanowski A.C. Schultz W. Adams E. Marsh Navy Center for Applied Research in Artificial Intelligence Naval Research Laboratory Inc. Washington D.C. DC USA

Intelligent mobile robots that interact with humans must exhibit adjustable autonomy; that is, the ability to dynamically adjust the level of self-sufficiency of an agent depending on the situation. When intelligent robots require close interactions with humans, they will require modes of communication that enhance the ability for humans to communicate naturally and that allow greater interaction, as well as adapt as a team member or sole agent in achieving various goals. Our previous work examined the use of multiple modes of communication, specifically natural language and gestures, to disambiguate the communication between a human and a robot. In this paper, we propose using context predicates to keep track of various goals during human-robot interactions. These context predicates allow the robot to maintain multiple goals, each with possibly different levels of required autonomy. They permit direct human interruption of the robot, while allowing the robot to smoothly return to a high level of autonomy.

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Dynamic issues for mobile robot real-time discovery and path planning

Dynamic issues for mobile robot real-time discovery and path...

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ieee international symposium on computational intelligence in robotics and automation (CIRA)

作者： J.S. Zelek School of Engineering University of Guelph Guelph ONT Canada

Sensor-based discovery path planning is the online guidance of a discovery agent (robot) who begins execution without a complete a priori map. The presented approach is locally optimal in the sense of minimizing the hitting probability while minimizing the distance to the goal based on what is currently known about the world. The technique is implemented as a process-based client-server. The integration and relationship between different facets of the algorithm are explored in terms of their effect on the real-time performance of the robot. The computation time for the minimal hitting probability surface is reduced by using methods of relaxation and a non-uniform sampling grid. The path is executed by a separate process reading gradient values off of the computed surface at regular intervals. Sensor updates are input as a collection of geometric primitives using a simple interface. Current work is focused on incorporating depth information from passive visual sensors.

关键词： Mobile robots Path planning Robot sensing systems Navigation Humans Intelligent robots Heuristic algorithms computational efficiency Grid computing Sampling methods

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Next best view system in a 3D object modeling task

Next best view system in a 3D object modeling task

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ieee international symposium on computational intelligence in robotics and automation (CIRA)

作者： L.M. Wong C. Dumont M.A. Abidi Department of Electrical and Computer Engineering IRIS Laboratory Knoxville TN USA

Sensor placement for 3D modeling is a growing area of computer vision and robotics. The objective of a sensor placement system is to make task-directed decisions for optimal pose selection. We propose a next best view solution to the sensor placement problem. Our algorithm computes the next best view by optimizing an objective function that measures the quantity of unknown information in each of a group of potential viewpoints. The potential views are either placed uniformly around the object or are calculated from the surface normals of the occupancy grid model. To initiate the collection of new data, the optimal pose is selected from the objective function calculation. The model is incrementally updated from the information acquired in each new view. This process terminates when the number of recovered voxels ceases to increase, yielding the final model. We tested two different algorithms on 8 objects of various complexity, including objects with simple concave, simple hole, and complex hole self-occlusions.

关键词： Cameras System software Image resolution Optimization methods Shape computational modeling Computer simulation Pixel

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A new correspondenceless geometric algorithm for motion estimation from range images

A new correspondenceless geometric algorithm for motion esti...

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ieee international symposium on computational intelligence in robotics and automation (CIRA)

作者： Yonghuai Liu M.A. Rodrigues AI and Pattern Recognition Research Group Department of Computer Science University of Hull Hull UK

A number of techniques for motion estimation from range images have been proposed over the past decade. A feature of existing techniques is that they do not explicitly use distance and angle information as rigid constraints to estimation. We have investigated the implications of this to the performance of algorithms and, in this paper, we propose a new correspondenceless algorithm for motion estimation from range images making full use of rigid constraints and projection information. The algorithm provides a closed form solution to all parameters of interest based on geometrical properties of correspondence vectors that have been synthesised into a single coordinate frame. For a comparative study of performance, we also implemented another correspondenceless motion estimation algorithm based on the eigenstructure analysis of the scatter matrix. Experimental results based on both synthetic and real images show that the proposed algorithm is accurate and robust and that it compares favourably with the scatter matrix algorithm.

关键词： Motion estimation Calibration Air cleaners Robustness Filters Cameras Scattering Quaternions Artificial intelligence Pattern recognition

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Cooperative navigation of micro-rovers using color segmentation

Cooperative navigation of micro-rovers using color segmentat...

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ieee international symposium on computational intelligence in robotics and automation (CIRA)

作者： J. Hyams M.W. Powell R. Murphy Department of Computer Science and Engineering University of South Florida Tampa FL USA

This paper addresses position estimation of a micro-rover mobile robot (called the "daughter") as a larger robot (the "mother") tracks it through large spaces with unstructured lighting. Position estimation is necessary for localization, where the mother extracts the relative position of the daughter for mapping purposes, and for cooperative navigation, where the mother controls the daughter in real-time. The approach taken is to employ the spherical coordinate transform color segmenter developed for medical applications as a low computational and hardware cost solution. Data was collected from 50 images taken in five types of lighting: fluorescent, tungsten, daylight lamp, natural daylight indoors and outdoors. The results show that average pixel error was 1.5, with an average error in distance estimation of 6.3 cm. The size of the error did not vary greatly with the type of lighting. The segmentation and distance tracking have also been implemented as a real-time tracking system. Using this system, the mother robot is able to autonomously control the micro-rover and display a map of the daughter's path.

关键词： Navigation Mobile robots Robot kinematics Image segmentation Orbital robotics Data mining Medical services Biomedical equipment Hardware computational efficiency

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Learning policies for attentional control

Learning policies for attentional control

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ieee international symposium on computational intelligence in robotics and automation (CIRA)

作者： L.M.G. Goncalves G.A. Giraldi A.A.F. Oliveira R.A. Grupen Laboratorio de Computacao Grafica-COPPE Sistemas Universidade Federal do Rio de Janeiro Rio de Janeiro Brazil Laboratory for Perceptual Robotics-Department of Computer Science University of Massachusetts Amherst MA USA

We propose two behaviourally active policies for attentional control. These policies must act based on a multi-modal sensory feedback. Two approaches are used to derive the policies: 1) a simple straightforward strategy, and 2) using Q-learning to learn a policy based on the perceptual state of the system. As a practical result of both algorithms, a robotic agent is capable to select a region of interest and perform shifts of attention focusing on the selected region. Then, a multi-feature extraction can take place allowing the system to identify or recognize a pattern representing that region of interest. Also, the policies have the desired property that all objects in the environment are visited at least once, although some of them can be visited more. In this way a robotic agent can relate sensed information to actions, abstracting and providing a feedback (categorization and mapping) for environmental stimuli.

关键词： Robot sensing systems Feedback Laboratories Computer science Pattern recognition Eyes Arm System testing Inspection Object detection

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Intelligent learning for deformable object manipulation

Intelligent learning for deformable object manipulation

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ieee international symposium on computational intelligence in robotics and automation (CIRA)

作者： A.M. Howard G.A. Bekey Institute for Robotics and Intelligent Systems School of Engineering University of Southern California Los Angeles CA USA

This paper addresses the problem of robotic grasping and manipulation of 3D deformable objects, such as rubber balls or bags filled with sand. Specifically, we have developed a generalized learning algorithm for handling of 3D deformable objects in which prior knowledge of object attributes is not required and thus it can be applied to a large class of object types. Our methodology relies on the implementation of two main tasks: to calculate deformation characteristics for a non-rigid object represented by a physically-based model; and to calculate the minimum force required to successfully lift the deformable object. This minimum lifting force can be learned using a technique called 'iterative lifting'. Once the deformation characteristics and the associated lifting force term are determined, they are used to train a neural network for extracting the minimum force required for subsequent deformable object manipulation tasks. Our developed algorithm has been validated by experiments.

关键词： Intelligent robots Rubber Deformable models Shape Intelligent systems Design engineering Systems engineering and theory Nonlinear equations Neural networks Iterative algorithms

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The body impedance control for walking stabilization of a quadrupedal robot

The body impedance control for walking stabilization of a qu...

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ieee international symposium on computational intelligence in robotics and automation (CIRA)

作者： Soo-Yeong Yi Yeh-Sun Hong Chong-Won Lee School of Electrical Engineering Chonbuk National University of Korea Cheongju South Korea Advanced Robotics Research Center Korea Institute of Science and Technology Seoul South Korea

One of the basic assumptions in the static gait design for a walking robot is that the weight of a leg should be negligible compared to that of body, so that the total gravity center of the robot is not affected by the leg swing. Based on the assumption, the conventional static gait has been designed for the geometric body center of the robot to be inside of the support polygon which consists of each support leg's tip position. In a case that the leg is relatively heavy, however, while the body center is kept inside the support polygon, the total gravity center of the robot can be out of the support polygon, which causes instability in walking. In this paper, a body impedance control is proposed to make the total gravity center of robot track the pre-designed trajectory of the body center, so that the walking stability is secured even in the case that the leg weight has serious influence on the total gravity center of the robot.

关键词： Legged locomotion Impedance Leg Gravity Foot Robot sensing systems Force measurement Actuators Fluctuations Weight control

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Towards focused plan monitoring: a technique and an application to mobile robots

Towards focused plan monitoring: a technique and an applicat...

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ieee international symposium on computational intelligence in robotics and automation (CIRA)

作者： M.E. Pollack C. McCarthy Intelligent Systems Program University of Pittsburgh Pittsburgh PA USA Department of Computer Science University of Pittsburgh Pittsburgh PA USA

Until recently, techniques for AI plan generation relied on highly restrictive assumptions that were almost always violated in real-world environments; consequently, robot designers adopted reactive architectures and avoided AI planning techniques. Some recent research efforts have focused on obviating such assumptions by developing techniques that enable the generation and execution of plans in dynamic, uncertain environments. In this paper, we discuss one such technique, rationale-based monitoring, originally introduced by Veloso, Pollack, and Cox (1998), and describe our use of it in a simple mobile robot environment. We review the original approach, describe how it can be adapted for a causal-link planner, and provide experimental results demonstrating that it can lead to improved plans without consuming excessive overhead. We also describe our use of rationale-based monitoring in a mobile robot office-assistant project currently in progress.

关键词： Mobile robots Artificial intelligence Meeting planning Computerized monitoring Application software Computer science Intelligent systems Intelligent robots Computer architecture Process planning

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Learning to grasp by using visual information

Learning to grasp by using visual information

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ieee international symposium on computational intelligence in robotics and automation (CIRA)

作者： A. Anglani F. Taurisano R. de Giuseppe C. Distante Dipartimento di Ingegneria dell'Innovazione Università di Lecce Lecce Italy

This paper presents a solution to the problem of manipulation control: target identification and grasping. The proposed controller is designed for a real platform in combination with a monocular vision system. The objective of the controller is to learn an optimal policy to reach and to grasp a spherical object of known size, randomly placed in the environment. In order to accomplish this, the task has been treated as a reinforcement problem, in which the controller learns by a trial and error approach the situation-action mapping. The optimal policy is found by using the Q-learning algorithm, a model free reinforcement learning technique, that rewards actions that move the arm closer to the target. The vision system uses geometrical computation to simplify the segmentation of the moving target and determines an estimate of the target parameters. The simulated knowledge has been ported on the industrial robot manipulator PUMA 560. Experimental results demonstrate the effectiveness of the adaptive controller that does not require an explicit global target position using direct perception of the environment.

关键词： Machine vision Control systems Optimal control Size control Error correction Learning Computer vision computational modeling Electrical equipment industry Service robots

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