Controlling fnger impedance is critical for successful grasping. Understanding how humans achieve this is of great interest for learning about human motor control, as well as for applications in robotic grasping. Ther...
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(纸本)0958758379
Controlling fnger impedance is critical for successful grasping. Understanding how humans achieve this is of great interest for learning about human motor control, as well as for applications in robotic grasping. There have been a number of studies on finger impedance in both the robotics and biological fields. They almost exclusively consider only stiffness and viscosity. However, inertia may play an important role in certain grasps, and is important for calculation of the other impedance properties. This paper reports current progress of a project to create a geometric model of the hand for predicting hand/grasp inertia at different configurations (sensed by a glove that measures joint angles) during a variety of tasks.
A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. How...
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A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques.
A reported liability of the controller area network protocol is that it does not provide a clock synchronization service. Therefore, whenever a CAN-based distributed embedded system requires its nodes to have a common...
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A reported liability of the controller area network protocol is that it does not provide a clock synchronization service. Therefore, whenever a CAN-based distributed embedded system requires its nodes to have a common time base, clock synchronization has to be implemented by means of an external mechanism. In a previous work, we proposed a fault-tolerant and high-precision clock synchronization protocol for CAN. This paper shows the first steps towards the formal verification of this protocol. In particular, it presents a formal model that has been built with the UPPAAL model checker and discusses how clock drift and clock correction can be modeled with this tool
For meaningful interaction between a robot and a human, an autonomous robot must recognize whether the experienced situation is created by people or by the environment. Using only proprioceptive data from a mobile rob...
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For meaningful interaction between a robot and a human, an autonomous robot must recognize whether the experienced situation is created by people or by the environment. Using only proprioceptive data from a mobile robotic platform, we discover that it is possible to distinguish sensory data patterns involving interaction. These patterns are obtained whilst navigating varying environments, both human populated and unpopulated. The paper reports the initial set of trials using Roball, a spherical mobile robot. Also described is the experimental methodology currently followed to validate the hypothesis that child interaction can be perceived directly from navigation sensors onboard a robotic platform.
This paper presents a sensor fault detection and diagnosis system for autonomous helicopters. The system has been tested with the MARVIN autonomous helicopter. Fault detection is accomplished by evaluating any signifi...
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This paper presents a sensor fault detection and diagnosis system for autonomous helicopters. The system has been tested with the MARVIN autonomous helicopter. Fault detection is accomplished by evaluating any significant change in the behaviour of the vehicle with respect to the fault-free behaviour, which is estimated by using an observer. The effectiveness of the proposed approach is demonstrated by means of MARVIN experimental results.
In this paper, a multi-view face detection method based on real Adaboost algorithm is presented. Human faces are divided into several viewpoint categories according to their poses in 3D, and for each of these categori...
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In this paper, a multi-view face detection method based on real Adaboost algorithm is presented. Human faces are divided into several viewpoint categories according to their poses in 3D, and for each of these categories a form of weak classifiers in look-up-table (LUT) type is designed using Haar-like features that have confidences in real values as their outputs, and correspondingly its space of weak classifiers is constructed, from which the cascade face detector is learnt by using real Adaboost algorithm. For speed up, multi-resolution searching and pose prediction strategies are introduced. For frontal face detection, the experiments on CMU + MIT frontal face test set result in a correct rate of 94.5% with 57 false alarms;for multi-view face detection, the experiments on CMU profile face test set result in a correct rate of 89.8% with 221 false alarms. The average processing time on a PIV 2.4 GHz PC is about 80 ms for a 320 × 240-pixel image. It can be seen that the proposed method is very efficient and has significant value in application.
This work presents a new algorithm for determining the trajectory of a mobile robot and, simultaneously, creating a detailed volumetric 3D model of its workspace. The algorithm exclusively utilizes information provide...
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This work presents a new algorithm for determining the trajectory of a mobile robot and, simultaneously, creating a detailed volumetric 3D model of its workspace. The algorithm exclusively utilizes information provided by a single stereo vision system, avoiding thus the use both of more costly laser systems and error-prone odometry. Six-degrees-of-freedom egomotion is directly estimated from images acquired at relatively close positions along the robot's path. Thus, the algorithm can deal with both planar and uneven terrain in a natural way, without requiring extra processing stages or additional orientation sensors. The 3D model is based on an octree that encapsulates clouds of 3D points obtained through stereo vision, which are integrated after each egomotion stage. Every point has three spatial coordinates referred to a single frame, as well as true-color components. The spatial location of those points is continuously improved as new images are acquired and integrated into the model.
This paper proposes a new coordination algorithm for efficiently exploring an unknown environment with a team of mobile robots. The proposed technique subsequently applies a well-known unsupervised clustering algorith...
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This paper proposes a new coordination algorithm for efficiently exploring an unknown environment with a team of mobile robots. The proposed technique subsequently applies a well-known unsupervised clustering algorithm (k-means) in order to fairly divide the remaining unknown space into as many disjoint regions as available robots. Each robot is primarily responsible for exploring its assigned region and can help other robots on its way through. Unknown space is dynamically repartitioned as new areas are discovered by the team, balancing thus the overall workload among team members and naturally leading to greater dispersion over the environment and thus faster broad coverage than with previous greedy-like approaches, which guide robots based on maximum profit strategies that simply trade off between distance to the closest frontiers and amount of unknown cells likely to be discovered from them.
A wide variety of texture feature extraction methods have been proposed for texture based image classification and segmentation. These methods are typically evaluated over windows of the same size, the latter being us...
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