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This paper presents the project of a robotics teaching tool which was designed to be a playful tool for learning check. The relevance of this study is due to the fact the design of this tool have originated from an extracurricular vision of a group of students who contributed to the development of it and had robotics as a form of entertainment that belongs to their world outside of the classroom....
A framework is developed to construct computational models of the human motor system (HMS) using iterative learning control (ILC) update structures. Optimal models of movement are introduced using a cost function that is motivated by learned human motion results. Three general ILC update structures are derived that each generate the required limiting solution using different forms of experimental...
Most experiments on policy search for robotics focus on isolated tasks, where the experiment is split into two distinct phases: 1) the learning phase, where the robot learns the task through exploration; 2) the exploitation phase, where exploration is turned off, and the robot demonstrates its performance on the task it has learned. In this paper, we present an algorithm that enables robots to continually...
We introduce a way to program adaptive reactive systems, using behavioral, scenario-based programming. Extending the semantics of live sequence charts with reinforcements allows the programmer not only to specify what the system should do or must not do, but also what it should try to do, in an intuitive and incremental way. By integrating scenario-based programs with reinforcement learning methods,...
Recent work has shown that preplanned motor programs are released early from subcortical areas by the using a startling acoustic stimulus (SAS). Our question is whether this response might also contain a recently learned internal model, which draws on experience to predict and compensate for expected perturbations in a feedforward manner. Studies of adaptation to robotic forces have shown some evidence...
Robotics is increasingly used in rehabilitation therapy of the hemiparetic arm after stroke. Several studies performed adaptation experiments to gain more insight in the underlying learning processes. In these studies adaptation during reaching movements in different directions is assessed. No information about influence of direction on the amount of learning to these separate directions is present...
In this paper we present a method for learning new objects situated in uncontrolled and unstructured environments. Visual information only is usually not sufficient for a reliable segmentation and learning of unknown objects without any a priori information. We propose an approach in which the robot introduces additional information by manipulating the entities in the scene, thus generating sufficient...
In this paper, we demonstrate that simple interactions with objects in the environment leads to a manifestation of the perceptual properties of objects. This is achieved by deriving a condensed representation of the effects of actions (called effect prototypes in the paper), and investigating the relevance between perceptual features extracted from the objects and the actions that can be applied to...
We developed three interfaces to allow non-expert users to teach name for new visual objects and compare them through user's studies in term of learning efficiency.
A major problem with previous object tracking approaches is adapting object representations depending on scene context to account for changes in illumination, viewpoint changes, etc. To adapt our previous approach to deal with background changes, here we first derive some clusters from a training sequence and the corresponding object representations for those clusters. Next, for each frame of a separate...
In this article, a learning mechanism and a multimodal interface are presented. The learning mechanism allows the robot to learn concepts of the environment by human tutelage. The multimodal interface employs mechanisms of face detection, pose estimation, object saliency and speech recognition. The learning mechanism and multimodal interface are evaluated in the context of concept learning.
In order to produce robots which can interact more effectively with humans we propose that it is necessary for their cognitive processes to be grounded in the same perceptual elements as humans deal with. Perceptual symbol systems offer an attractive mechanism for capturing the symbolic properties of the senses and for integrating them into higher level cognitive processes. We have designed a perceptual...
For humanoid robots, the skill of gaze following is a foundational component in social interaction and imitation learning.We present a robotic system capable of learning the gaze following behavior in a real-world environment. First, the system learns to detect salient objects and to distinguish a caregiverpsilas head poses in a semi-autonomous manner. Then we present multiple scenes containing different...
How sequences of actions are learned, remembered, and generated is a core problem of cognition. Despite considerable theoretical work on serial order, it typically remains unexamined how physical agents may direct sequential actions at the environment within which they are embedded. Situated physical agents face a key problem - the need to accommodate variable amounts of time it takes to terminate...
Since body representation is one of the most fundamental issues for physical agents (humans, primates, and also robots) to adaptively perform various kinds of tasks, a number of learning methods have attempted to make robots acquire their body representation. However, these previous methods have supposed that the reference frame is given and fixed a priori. Therefore, such acquisition has not been...
To achieve truly autonomous robot skill acquisition, a robot can use neither a single large general state space (because learning is not feasible), nor a small problem-specific state space (because it is not general).We propose that instead a robot should have a set of sensorimotor abstractions that can be considered small candidate state spaces, and select one that is appropriate for learning a skill...
The ADAPT project is a collaboration of three universities building a unified architecture for mobile robots. The goal of this project is to endow robots with the full range of cognitive abilities, including perception, use of natural language, learning and the ability to solve complex problems. The perspective of this work is that such an architecture should be based on language and visualization...
This paper describes a model for visual homing. It uses Sarsa(lambda) as its learning algorithm, combined with the Jeffery divergence measure (JDM) as a way of terminating the task and augmenting the reward signal. The visual features are taken to be the histograms difference of the current view and the stored views of the goal location, taken for all RGB channels. A radial basis function layer acts...
Multiple autonomous robotic systems can be represented by multi-agent. In multi-agents systems, each agent must behave independently according to its states and environments, and, if necessary, must cooperate with other agents in order to perform a given task. In the present study, we focused on the problem of ldquotrash collectionrdquo, in which multiple agents collect all trash as quickly as possible...
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