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检索条件"机构=Computer Vision and Robotics Laboratory Computer Vision and Robotics Laboratory"

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Learning trajectory patterns by clustering: Experimental studies and comparative evaluation

Learning trajectory patterns by clustering: Experimental stu...

引用

Conference on computer vision and Pattern Recognition (CVPR)

作者： Brendan Morris Mohan Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego CA USA

Recently a large amount of research has been devoted to automatic activity analysis. Typically, activities have been defined by their motion characteristics and represented by trajectories. These trajectories are collected and clustered to determine typical behaviors. This paper evaluates different similarity measures and clustering methodologies to catalog their strengths and weaknesses when utilized for the trajectory learning problem. The clustering performance is measured by evaluating the correct clustering rate on different datasets with varying characteristics.

关键词： Principal component analysis Euclidean distance computer vision Prototypes Hidden Markov models Robot vision systems robotics and automation Laboratories Pattern analysis Layout

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Introducing “XMOB”: Extremity Movement Observation Framework for Upper Body Pose Tracking in 3D

Introducing “XMOB”: Extremity Movement Observation Framewo...

引用

IEEE International Symposium on Multimedia

作者： Cuong Tran Mohan M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego CA USA

We introduce a vision based, marker less upper body pose tracking approach that first tracks the 3D movements of extremities, including head and hands. Then based on the knowledge of upper body model, these extremity movements are used to predict the whole upper body motion as an inverse kinematics problem. The experimental validation showed the promise of applying this approach in several smart environments and HCI situations, e.g. user activity observation in driving scene, meeting room, teleconference scene.

关键词： Extremities Tracking Head Humans Kinematics Predictive models Layout Laboratories Teleconferencing Motion estimation

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On the generation of feasible paths for aerial robots in environments with obstacles

On the generation of feasible paths for aerial robots in env...

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2009 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Douglas G. Macharet Armando A. Neto Mario F. M. Campos Computer Vision and Robotics Laboratory (Ver lab) Computer Science Department Federal University of Minas Gerais Brazil

This paper presents a methodology based on a variation of the Rapidly-exploring Random Trees (RRTs) that generates feasible trajectories for autonomous aerial vehicles with holonomic constraints in environments with obstacles. Our approach uses Pythagorean Hodograph (PH) curves to connect vertices of the tree, which makes it possible to generate paths for which the main kinematic constraints of the vehicle are not violated. The smoothness of the acceleration profile of the vehicle is indirectly guaranteed between two vertices of the RRT tree. The proposed algorithm provides fast convergence to the final trajectory. We still utilize the properties of the RRT to avoid collisions with static obstacles of a environment. We show results for a small unmanned aerial vehicles in environments with different configurations.

关键词： Unmanned aerial vehicles Remotely operated vehicles Space vehicles Aircraft Mobile robots Path planning Intelligent robots Trajectory USA Councils Kinematics

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Head and gaze dynamics in visual attention and context learning

Head and gaze dynamics in visual attention and context learn...

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IEEE computer Society Conference on computer vision and Pattern Recognition Workshops (CVPRW)

作者： Anup Doshi Mohan M. Trivedi Laboratory for Intelligent and Safe Automobiles Computer Vision and Robotics Research Laboratory University of California San Diego USA

Future intelligent environments and systems may need to interact with humans while simultaneously analyzing events and critical situations. Assistive living, advanced driver assistance systems, and intelligent command-and-control centers are just a few of these cases where human interactions play a critical role in situation analysis. In particular, the behavior or body language of the human subject may be a strong indicator of the context of the situation. In this paper we demonstrate how the interaction of a human observer's head pose and eye gaze behaviors can provide significant insight into the context of the event. Such semantic data derived from human behaviors can be used to help interpret and recognize an ongoing event. We present examples from driving and intelligent meeting rooms to support these conclusions, and demonstrate how to use these techniques to improve contextual learning.

关键词： Humans Intelligent systems Intelligent robots Layout Monitoring Air traffic control Vehicle dynamics Cameras Laboratories Intelligent vehicles

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Traffic control for a swarm of robots: Avoiding target congestion

Traffic control for a swarm of robots: Avoiding target conge...

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2009 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Leandro Soriano Marcolino Luiz Chaimowicz Vision and Robotics Laboratory (VeRLab) Computer Science Department Federal University of Minas Gerais Brazil

One of the main problems in the navigation of robotic swarms is when several robots try to reach the same target at the same time, causing congestion situations that may compromise performance. In this paper, we propose a distributed coordination algorithm to alleviate this type of congestion. Using local sensing and communication, and controlling their actions using a probabilistic finite state machine, robots are able to coordinate themselves to avoid these situations. Simulations and real experiments were executed to study the performance and effectiveness of the proposed algorithm. Results show that the algorithm allows the swarm to have a more efficient and smoother navigation and is suitable for large groups of robots.

关键词： Traffic control Robot kinematics Navigation Robot sensing systems Intelligent robots Automata Robustness Roads Collision avoidance USA Councils

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Traffic control for a swarm of robots: Avoiding group conflicts

Traffic control for a swarm of robots: Avoiding group confli...

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2009 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Leandro Soriano Marcolino Luiz Chaimowicz Vision and Robotics Laboratory (VeRLab) Computer Science Department Federal University of Minas Gerais Brazil

A very common problem in the navigation of robotic swarms is when groups of robots move into opposite directions, causing congestion situations that may compromise performance. In this paper, we propose a distributed coordination algorithm to alleviate this type of congestion. By working collaboratively, and warning their teammates about a congestion risk, robots are able to coordinate themselves to avoid these situations. We executed simulations and real experiments to study the performance and effectiveness of the proposed algorithm. Results show that the algorithm allows the swarm to navigate in a smoother and more efficient fashion, and is suitable for large groups of robots.

关键词： Traffic control Robot kinematics Navigation Intelligent robots Robot sensing systems Collision avoidance Orbital robotics Distributed algorithms USA Councils Collaborative work

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A path planning algorithm for UAVs with limited climb angle

A path planning algorithm for UAVs with limited climb angle

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2009 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Armando A. Neto Mario F. M. Campos Vision and Robotics Laboratory (Verlab) Computer Science Department Federal University of Minas Gerais Brazil

In this paper we present a methodology based on a variation of the spatial pythagorean hodograph curves to generate smooth feasible paths for autonomous vehicles in three-dimensional space under the restriction of limited climb angles. An fast iterative algorithm is used to calculate the curve. The generated path satisfy three main angular constraints given by the vehicle: (i) maximum curvature, (ii) maximum torsion and (iii) maximum climb (or dive). A path is considered feasible if these kinematic constraints are not violated. The smoothness vehicle's acceleration profile is indirectly guaranteed between two points. The proposed methodology is applicable to vehicles that move in three-dimensional environments, and that can be modeled by the constraints considered here. We show results for small aerial vehicle.

关键词： Path planning Unmanned aerial vehicles Remotely operated vehicles Space vehicles Mobile robots Interpolation Iterative algorithms Kinematics Acceleration Aircraft

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Unsupervised learning of motion patterns of rear surrounding vehicles

Unsupervised learning of motion patterns of rear surrounding...

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IEEE International Conference on Vehicular Electronics and Safety (ICVES)

作者： Brendan Morris Mohan Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego La Jolla CA USA

Awareness to a vehicle's surrounding is necessary for safe driving. Current surround technologies focus on the detection of obstacles in hard-to-view places but may neglect temporal information. This paper seeks the causes of dangerous situations by examining surround behavior. A general hierarchical learning framework is introduced to automatically learn surround behaviors. By observing motion trajectories during natural driving, models of rear vehicle behaviors are obtained in an unsupervised fashion. The extracted behaviors are shown to correspond to typical driving scenarios, vehicle overtake and surround overtake, demonstrating the effectiveness of the learning framework.

关键词： Unsupervised learning Vehicles

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A framework for automating the construction of computational models

A framework for automating the construction of computational...

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Congress on Evolutionary Computation

作者： E. Hourdakis P. Trahanias Department of Computer Science University of Crete Greece Computational Vision and Robotics Laboratory Foundation for Research and Technology - Hellas Heraklion Greece

Computational modeling of natural systems can be used for interdisciplinary applications, such as the configuration of robotic systems or the validation of biological ones. Up to date there has been a little progress on suggesting a framework for automating the process of creating a computational model for biological processes. Instead researchers focus on the implementations of systems that are intended to replicate a tight set of biological behaviors. Such framework should be able to construct any system based on the appropriate level of abstraction chosen by the designer, as well as be able to enforce the appropriate biological consistency without compromising on performance or scalability of the generated models. In this paper we propose a framework that can automate the construction of computational models using genetic algorithms and demonstrate how this framework can construct a model of the parieto-frontal and premotor regions involved in grasping.

关键词： Computational modeling Biological system modeling Biology computing Biological systems computer science Brain modeling Genetic algorithms computer vision Robot vision systems Laboratories

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Quantifying perception of nonlinear elastic tissue models using multidimensional scaling

Quantifying perception of nonlinear elastic tissue models us...

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World Haptics Conference

作者： Sarthak Misra Philipp Fuernstahl K. T. Ramesh Allison M. Okamura Matthias Harders Laboratory of Computational Sensing & Robotics Johns Hopkins University Baltimore MD USA Virtual Reality in Medicine Group Computer Vision Laboratory ETH Zurich Zurich Switzerland

Simplified soft tissue models used in surgical simulations cannot perfectly reproduce all material behaviors. In particular, many tissues exhibit the Poynting effect, which results in normal forces during shearing of tissue and is only observed in nonlinear elastic material models. In order to investigate and quantify the role of the Poynting effect on material discrimination, we performed a multi-dimensional scaling (MDS) study. Participants were presented with several pairs of shear and normal forces generated by a haptic device during interaction with virtual soft objects. Participants were asked to rate the similarity between the forces felt. The selection of the material parameters - and thus the magnitude of the shear and normal forces - was based on a pre-study prior to the MDS experiment. It was observed that for nonlinear elastic tissue models exhibiting the Poynting effect, MDS analysis indicated that both shear and normal forces affect user perception.

关键词： Multidimensional systems Surgery Computational modeling Haptic interfaces Biological materials Shearing Humans computer simulation computer vision Biological tissues

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