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To achieve human-like motion of the humanoid robots we propose an approach for robot skill-synthesis that exploits human visuo-motor learning capacity. The conceptual idea is to consider the target robot platform as a tool that can be intuitively controlled by a human. Once the robot is effortlessly controlled, the target behaviour of the robot is obtained by the human through practice. Subsequently...
The direct perception of actions allows a robot to predict the afforded actions of observed objects. In this paper, we present a non-parametric approach to representing the affordance-bearing subparts of objects. This representation forms the basis of a kernel function for computing the similarity between different subparts. Using this kernel function, together with motor primitive actions, the robot...
Transferring human skills to dextrous robots in an easy, fast and robust way is one of the key challenges that still have to be tackled in order to bring robots to our every-day life. However, many problems remain unsolved. In particular, researchers are seeking new paradigms along with efficient and robust task representations that facilitate adaptation to new contexts and provide a means to appropriately...
In most activities of daily living, related tasks are encountered over and over again. This regularity allows humans and robots to reuse existing solutions for known recurring tasks. We expect that reusing a set of standard solutions to solve similar tasks will facilitate the design and on-line adaptation of the control systems of robots operating in human environments. In this paper, we derive a...
The notion of affordances that was proposed by J.J. Gibson, refers to the action possibilities offered to the organism by its environment. In a previous formalization, affordances are defined as general relations that pertain to the robot-environment interaction and they are represented as triples which consist of the initial percept of the environment, the behavior applied and the effect produced...
We know various strategies toward teaching and controlling humanoid robots. Some refer to direct joint or tip control and others use more intuitive approach such as mimicking human motion in a certain task. This kind of robot control, where a robot is considered a tool, controlled by a human demonstrator, is called visuo-motion control. In this paper, we present an improved approach to overcome a...
In this paper we describe and experimentally evaluate how to model, control, and use the capabilities of a humanoid visual system with foveated vision. We present a computational process that can be utilized to identify and update the parameters of the robot's eyes under motion, which enables the use of 3D vision on an active humanoid head. We also derive the formulas expressing the geometry of our...
In this study we report our preliminary work on investigating task dependent grasping in humans and realization of this skill on a robotic platform. For human data acquisition, subjects were asked to reach and grasp two objects (a claw-hammer and a pen) positioned in four different orientations. The subjects were primed by specification of the task to be performed with the objects after the grasp...
A cognitive robot system has to acquire and efficiently store vast knowledge about the world it operates in. To cope with every day tasks, a robot needs to learn, classify and recognize a manifold of different objects. Our work focuses on an object representation scheme that allows storing perceived objects in a compact way. This will enable the system to store extensive information about the world...
We propose a framework for skill synthesis for robots that exploits the human capacity to learn novel control tasks. The conceptual idea is to incorporate the target robotic platform into the experimenter's body schema so that it can be controlled effortlessly as if the robot were a part of the body. Once this stage is achieved, the dexterity on a task exhibited with the new external limb -the robot-...
For humanoid robots to be part of our daily lives, not only mobility and their manipulation capability being essential, but their ability to represent and recognize objects in an adaptable manner is also crucial. To this end, we propose an object representation scheme that fits well with the view-based cortical representation of objects found in the primate inferotemporal cortex (IT). We derive our...
If humanoid robots are to become commonplace in our society, it is important to understand how they are perceived by humans. An influent model in social cognitive neuroscience posits that in human face-to-face interaction, the observation of another individual performing an action facilitates the execution of a similar action, and interferes with the execution of different action. In one interference...
Imitation is a vast topic for both human sciences and robotics. Recent advances in the understanding of the neural mechanisms of imitation offer methodologies that bring the two research domains closer. In this paper we analyze how an imitation system can be bootstrapped from a non-imitative system at an abstract level so that the ideas derived can be applicable to infant development as well as robotics...
The article contributes to the quest to relate global data on brain and behavior (e.g. from PET, Positron Emission Tomography, and fMRI, functional Magnetic Resonance Imaging) to the underpinning neural networks. Models tied to human brain imaging data often focus on a few “boxes” based on brain regions associated with exceptionally high blood flow, rather than analyzing the cooperative computation...
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