The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
We show that inverse kinematics of different tools can be efficiently learned with a single recurrent neural network. Our model exploits all upper body degrees of freedom of the Honda's humanoid robot research platform. Both hands are controlled at the same time with parametrized tool geometry. We show that generalization both in space as well as across tools is possible from very few training data...
We model the dynamics of non-linear point-to-point robot motions as a time-independent system described by an autonomous dynamical system (DS). We propose an iterative algorithm to estimate the form of the DS through a mixture of Gaussian distributions. We prove that the resulting model is asymptotically stable at the target. We validate the accuracy of the model on a library of 2D human motions and...
We present a dynamical system approach that couples task and joint space by means of an attractor-based content addressable memory. The respective recurrent reservoir network simultaneously provides a novel control framework for goal directed movement generation. The network first learns to associate end effector coordinates with joint angles by means of reservoir attractor states and thereby implements...
Analytic modeling, imitation, and experience-based learning are three approaches that enable robots to acquire models of their morphology and skills. In this paper, we combine these three approaches to efficiently gather training data to learn a model of reachability for a typical mobile manipulation task: approaching a worksurface in order to grasp an object. The core of the approach is experience-based...
This paper presents a rehabilitation robot used for the patient with paralysis of lower limb and the kinematics of the mechanism is analyzed. The mechanical design of the robot is described. The forward and inverse kinematics solution of the robot is given. The working space of the foot apex is calculated under the training range. The trajectory planning is studied. It provides important data reference...
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 present a neural network approach to early motor learning. The goal is to explore the needs for boot-strapping the control of hand movements in a biologically plausible learning scenario. The model is applied to the control of hand postures of the humanoid robot ASIMO by means of full upper body movements. For training, we use an efficient online scheme for recurrent reservoir networks consisting...
The present work focuses on perceptual control of haptic manipulation during high frequency interaction with mobile objects. In particular in this work we focused on the analysis of the control and perceptual issues in the throwing and catching in juggling. A training multimodal system that exploits the concepts of co-located visuo-haptic feedback and encountered interfaces was implemented. Using...
This paper describes the design and application of an omnidirectional lower limbs rehabilitation training robot. The robot is designed to improve patient walking ability, who suffers from impairment in locomotion after neurology injuries. The robot is characterized with three key points as follows: (1) omnidirectional wheeled mechanical structure, (2) real-time biofeedback mechanism, and (3) balance...
Robot soccer is an excellent testbed to explore innovative ideas and test the algorithms in multi-agent systems (MAS) research. A soccer team should play in an organized manner in order to score more goals than the opponent, which requires well-developed individual and collaborative skills, such as dribbling the ball, positioning, and passing. However, none of these skills needs to be perfect and...
This paper presents the design, and performance of a high fidelity three degree-of-freedom wrist exoskeleton robot, for neuroscience study, training and rehabilitation. The IIT-Wrist is intended to provide kinesthetic feedback during the training of motor skills or rehabilitation of reaching movements. Motivation for such applications is based on findings that show robot-assisted physical therapy...
This paper we propose a new rehabilitation training support system of upper limbs with the teaching/training function for personalized rehabilitation. The proposed teaching/training function enables the therapists to easily make not only training trajectories but also training programs to suit the individual needs of the patients. It is shown in this paper that three kinds of training programs requested...
In this paper, a reliable, fast and robust approach for static hand gesture recognition in the domain of a human-robot interaction system is presented. The method is based on computing the likelihood of different existing gesture-types and assigning a probability to every type by using Bayesian inference rules. For this purpose, two classes of geometrical invariants has been defined and the gesture...
The objective of practical training is a major issue in students education, in many engineering disciplines. The access to specialized technological equipment for education is often limited by specific time restriction, or not provided at all. Therefore, the benefits by providing a Web-based platform for remote experimentation via LAN or Internet are evident. This paper describes the development of...
This paper focuses on developing a team of mobile robots capable of learning via human interaction. A modified Q-learning algorithm incorporating a teacher is proposed. The paper first concentrates on simplifying the Q-learning algorithm to be implemented on small and simple team of robots having limited capabilities of memory and computational power. Second it concentrates on the incorporation of...
Reservoir computing (RC) uses a randomly created Recurrent Neural Network as a reservoir of rich dynamics which projects the input to a high dimensional space. These projections are mapped to the desired output using a linear output layer, which is the only part being trained by standard linear regression. In this work, RC is used for imitation learning of multiple behaviors which are generated by...
Up to now, different kinds of musical performance robots have been developed. MPRs are designed to closely reproduce the human organs involved during the playing of musical instruments. Our research on the Waseda Flutist Robot has been focused on clarifying the human motor control from an engineering point of view. As a result, the Waseda Flutist Robot No. 4 Refined IV (WF-4RIV) is able of playing...
Task-oriented repetitive movements can improve motor recovery in patients with neurological or orthopaedic lesions. HEnRiE is a robot based haptic environment for simultaneous training of reaching and grasping movements. It consists of a robot with three active and two passive degrees of freedom and a grasping device with one degree of freedom. A training scenario that includes a virtual physiotherapist...
Rehabilitation robots start to become an important tool in stroke rehabilitation. Compared to manual arm training, robot-supported training can be more intensive, of longer duration, repetitive and task-oriented. Therefore, these devices have the potential to improve the rehabilitation process in stroke patients. While in the past, most groups have been working with endeffector-based robots, exoskeleton...
This paper describes how the clustering topology of an input space data distribution is utilized to properly initialize an adaptive neuro-fuzzy inference system (ANFIS). We used a new unsupervised clustering algorithm called topology based fuzzy clustering (TFC) that performs better than growing neural gas (GNG) in extracting the input-space topology. The topology information in the form of number...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.