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During the past years, face and gait recognition in video have received significant attention. Consequently, their recognition problems have challenged due to largely varying appearances and highly complex pattern distributions. However, the complementary properties of these two biometrics suggest fusion of them. Face recognition is more reliable when the person is close to the camera. On the other...
Robots that interact with humans in everyday situations, need to be able to interpret the nonverbal social cues of their human interaction partners. We show that humans use body posture and head pose as social signals to initiate and terminate interaction when ordering drinks at a bar. For that, we record and analyze 108 interactions of humans interacting with a human bartender. Based on these findings,...
This paper presents a possibility that we can teach what emotions a robot should express. For this, we design an artificial emotion decision system learned by feedbacks of users. The proposed system consists of three parts: a personality space with probability model, an emotion decision process, and an emotion learning process. 1) The personality space is designed based on the Five-Factor Model. In...
Emotional interaction with human beings is desirable for robots. In this study, we propose an integrated system which has ability to track multiple people at the same time, to recognize their facial expressions, and to identify social atmosphere. Consequently, robots can easily recognize facial expression, emotion variations of different people, and can respond properly.
Passive velocity field control is advantageous to deliver human-in-the-loop contour tracking rehabilitation exercises, since patients can be allowed to proceed with their preferred pace, while assistance can still be provided as determined by the therapist with ensured coupled stability. We introduce a framework based on passive velocity field control for robot assisted rehabilitation that includes...
Human motion prediction is becoming more and more important issue in the filed of wearable robots or biorobotics. This paper provides an initial experimental result for human motion prediction. In detail, the prediction method for ternary choice among rock-paper-scissors is presented using temporal patterns of muscle activations (Electromyography, in short EMG) controlling hand motion of subject....
This work extends the framework of bilateral shared control of mobile robots with the aim of increasing the robot autonomy and decreasing the operator commitment. We consider persistent autonomous behaviors where a cyclic motion must be executed by the robot. The human operator is in charge of modifying online some geometric properties of the desired path. This is then autonomously processed by the...
We address the problem of robot participation as a team member in group activities. In this human-robot interactive setting, the goal is to enable a robot to detect objects around it using on-board video cameras, and determine which activity they are performing. It then determines how it should move to participate in the activity based on its intended role, derived from domain knowledge, and human...
This paper presents tracking algorithms of a mobile robot that tracks a human in front. The mobile robot, which is a differential-driven wheel type, is equipped with a laser range finder to perform human tracking in front. Initially, we recommend the torso part for the robust tracking of the human body in outdoor environment by a laser range finder. To track a human in front, we define a virtual target...
In this paper, we propose an online algorithm for multimodal categorization based on the autonomously acquired multimodal information and partial words given by human users. For multimodal concept formation, multimodal latent Dirichlet allocation (MLDA) using Gibbs sampling is extended to an online version. We introduce a particle filter, which significantly improve the performance of the online MLDA,...
We present an approach, based on non-negative matrix factorization, for learning to recognize parallel combinations of initially unknown human motion primitives, associated with ambiguous sets of linguistic labels during training. In the training phase, the learner observes a human producing complex motions which are parallel combinations of initially unknown motion primitives. Each time the human...
In this paper, we propose a passive wire-type motion support system to guide a human hand through the use of servo brakes. This system is intrinsically safe because servo brakes cannot generate a driving force to control the system. On the other hand, this system may not generate sufficient force to guide the human hand along the desired path because of the use of servo brakes. To resolve this problem,...
With the increasing development of complex technical systems such as power supply systems or human-machine-interaction systems, their availability, reliability and safety are always a special interest of researches. In recent years, the concept of human-centered guidance and control has been introduced into the complex technical systems to solve the growing complexity in interdependencies, uncertainties...
Center of mass (CoM) trajectory is important during standing and walking since it can be used as an index for stability and fall prediction. Unfortunately current methods for CoM estimation require the use of specialized equipment (such as motion capture and force platforms) in controlled environments. This paper aims at applying the statically equivalent serial chain (SESC) method to obtain CoM position...
Research in Information Retrieval (IR) experienced a paradigm shift from first having too few documents to search from to now having way too many of them. When users have trouble finding relevant documents, they tend to become frustrated and give up searching. Scholars have attempted to reduce instances of search frustration via query expansion, information filtering, and incorporating user feedback...
Multi-fingered robot grasping is a challenging problem that is difficult to tackle using hand-coded programs. In this paper we present an imitation learning approach for learning and generalizing grasping skills based on human demonstrations. To this end, we split the task of synthesizing a grasping motion into three parts: (1) learning efficient grasp representations from human demonstrations, (2)...
This paper presents a method for achieving stable “human-like” running in simulation by using human-inspired control. Data from human running experiments are processed, analyzed and split into the two domains: stance phase and flight phase. By examining this data, we present a set of outputs, i.e., functions of the kinematics, which appear to represent human running; moreover, we show that this output...
Reaching is a fundamental skill for a robot. The purpose of robot reaching is to bring a robot hand to an object without any obstacle collision. Conventional handcrafted methods were complicated to implement reaching skill. Thus, this paper proposes a method using primitives acquired from human demonstrations to learn collision-free reaching skill. End-effector and joint trajectories of primitives...
Humans exhibit exceptional skills in using tools and manipulating objects of their environment by skillfully controlling exerted force and arm impedance. One of the basic components of this mechanism is the generation of internal models which associate kinematic variables with applied force. On the other hand, making robots capable of skillfully using tools and adapting their motor behavior to new...
This study focuses on joint motion patterns of humans that move together with other humans or objects. Since this scope embraces ‘group motion’, which relates only humans, and expands its extent of interactions accounting for various auxiliary instruments such as walking aids or pushcarts, we term this collective motion pattern as ‘coherent’ motion. Coherence is proposed to be characterized by the...
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