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Is low-cost tracking precise enough for recognition of pointing actions? We investigate the quality of the human body tracking available with a Kinect camera by comparing it to a state-of-the-art motion capture system. The application is action recognition with parametric hidden Markov Models (PHMMs) for programming industrial robots. The data from the Kinect is overall more noisy and potentially...
This paper is concerned with the problem of teleoperation systems over networks. As is well known, quantization and time delay are unavoidable in computer network communications. Compared with previous work, we consider both of them when analyzing such systems. The controller used in this paper is proportional-derivative(PD) controller, but the output signals of master and slave systems are quantized...
Physical human-robot interaction between a human leader and a robot follower in waltz is studied in this paper. The dancers' body dynamics in single-support phase are modeled as inverted pendulums. On the robot side, an ankle torque control method is proposed and applied. The control law forms a time-dependent vector field, which makes the nominal orbit of the robot to be an attractor. To physically...
Reaching to an object is a fundamental skill to a robot. The purpose of robot reaching aims at bringing the robot hands to the object location without obstacle collision. Since implementing such robot reaching movement is a tedious task, this paper proposes a method to synthesize robot reaching movement by human demonstration. However, human demonstrations are inconsistent, this paper adopts Gaussian...
This paper proposes a simplified integrated reproduction of saved motion components. For storing and reproduction of haptic information, a motion-copying system was proposed. By the motion-copying system, for example, techniques of experts can be reproduced by robots to improve work efficiency. In the skill reproduction by robots, it is possible to reproduce the various motion by integration of the...
This paper aims at stimulating the discussion on the future of Intelligent Vehicles. It is a position paper, indicating converging technologies that, in our opinion, will have to be used in future Intelligent Vehicles. We present a vision according to which Intelligent Vehicles will evolve into Human-peer Robots, here called Co-Drivers. Co-Drivers will be able to “understand” human drivers and to...
The paper presents a new online incremental zero-shot learning method for applications in robotics and mobile communications where attribute labeling is obtained via online interaction with users, and where the potential for inconsistency exists. Unique to most previous offline batch learning methods, the proposed method is based on the indirect-attribute-prediction (IAP) model instead of the direct-attribute-prediction...
To investigate fast human reaching movements in 3D, we asked 11 right-handed persons to catch a tennis ball while we tracked the movements of their arms. To ensure consistent trajectories of the ball, we used a catapult to throw the ball from three different positions. Tangential velocity profiles of the hand were in general bell-shaped and hand movements in 3D coincided with well known results for...
This paper presents a novel method to characterize mechanical impedance of a human joint. We employed a non-parametric stochastic identification method and an interactive robot. This method allows us to determine several important properties including a) joint impedance in the direction of the joint principal axes, b) the spatial joint impedance structure, and c) the passivity properties of the joint...
Given the remarkable recent progress in robotics research, we can envision the day when robots and humans coexist and robots become closely integrated into our daily lives. This means endowing robots with the ability to communicate so they perceive human emotion, adapt their behavior to humans, and sense situations even without explicit instructions. Meanwhile, affective computing, that interprets...
Generally, CMAC (Cerebellar Model Articulation Controller) is used for learning of robot action, because of high speed and low memories. However, results obtained by learning are hard to understand for human because they are numeric data. We research skill acquisition of an operator by using CMAC in our laboratory. In this research, we conducted the rule extraction by Fuzzy Neural Network (FNN) from...
With the spreading of intelligent machines, manmachine co-operation has become an important research area. Today, intelligent robots collaborating with humans usually have to be able to store, retrieve, and update information about their environment, interpret and execute commands, offer existing and gain/learn new services. In these processes, the efficient knowledge representation and storage are...
In a previous study, stability of a spring-mass hopping-model with variable rest length and stiffness during stance has been investigated. Here, robustness of the stable hopping solutions is addressed. For this, the basin of attraction of the stable fixed points is determined. Results show a tradeoff between maximum stability and maximum robustness. Additional velocity-dependent damping only slightly...
A general problem for human-machine interaction occurs when a machine's controllable dimensions outnumber the control channels available to its human user. In this work, we examine one prominent example of this problem: amputee switching between the multiple functions of a powered artificial limb. We propose a dynamic switching approach that learns during ongoing interaction to anticipate user behaviour,...
There are millions of people that regularly play Go in many countries around the world. Played by two players, Black and White, the stones of their colors are placed consecutively on an empty intersection of a square grid. In order to support beginners of Go to enjoy and concentrate on the game, this paper proposes a fuzzy markup language (FML)-based emotional expression system and applies it to computer...
Affective computing is computing that relates to, arises from, or deliberately influences emotions. It has lots of applications in the next generation of human-computer interfaces. We have proposed a closed-loop affective computing system, which includes affect recognition, affect modeling, and affect control. Because emotions include both intra-personal uncertainty, which is the uncertainty a person...
Intention recognition plays a key role in the cooperation among the humans. An intention describes an action or sequence of actions to be performed for achieving the intended purpose. The cooperating humans learn each others intentions while cooperation. In this paper we propose three ways how a robot can learn the intention of the cooperating human. In the first case, the robot learns the human intention...
The studies on mirror neurons observed in monkeys indicate that recognition of other's actions activates neural circuits that are also responsible for generating the very same actions in the animal. The mirror neuron hypothesis argues that such an overlap between action generation and recognition can provide a shared worldview among individuals and be a key pillar for communication. Inspired by these...
In this paper, a method to derive the three predominant synergies and their temporal weights for planning grasps of the UB Hand IV (University of Bologna Hand, version IV) is proposed. The method adopted to define the postural synergies from experiments is based on the kinematic structure of the robotic hand and on the taxonomy of the grasps of common objects. The control strategy, exploiting postural...
We present an approach to automatically learn the visual appearance of an environment in terms of object classes. The procedure is totally unsupervised, incremental, and can be executed in real time. The traversability property of an unseen object is also learnt without human supervision by the interaction between the robot and the environment. An incremental version of affinity propagation, a state-of-the-art...
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