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A robot is presented whose behavior is based on two fundamental types of learning in the animal world: Classical Conditioning (CC) and Operant Conditioning (OC). It is shown how both share Spike-Timing-Dependent-Plasticity (STDP) as learning process for a Spiking Neural Network (SNN). STDP was implemented on a Field-Programmable Gate Array (FPGA) with very low-demanding resources, using an adaptation...
My PhD research aims to develop a general framework for a behavior control architecture that will provide customized interaction between the robot and an elderly individual suffering from mild cognitive impairment (MCI). This framework will enable the robot to learn from past events and to adapt its behavior to the specific needs of the person that it interacts with. For this purpose, models will...
Mobile devices in industrial settings became commonplace with different handheld equipment and mobile robots using COTS WiFi interfaces for communication. This growth in the use of the wireless medium increases the potential for overload and consequent long delays and high losses. Traffic segregation with different Quality of Service (QoS) classes can attenuate the problem but does not solve it within...
A method of a control system synthesis for the separate UR thruster is developed. A special non-linear correcting device and adaptive adjustment on reference model are applied for non-linearity compensating and required quality of control processes saving at change of thruster parameters in a given range. A new approach to forming a self-adjustment signal ensuring activity in a linear zone of the...
This paper proposes a technique of on-line modeling for feedforward (FF) learning control. For an unknown nonlinear multi-input multi-output (MIMO) plant which is free of zero dynamics, we construct a bank of filters each of which corresponds to a local model of inverse dynamics. In real time we select one such filter corresponding to the current operating point (called scheduler) and accumulate input-output...
Learning is essential for an autonomous agent to adapt to an environment. One method of learning is through trial and error, however, this method is impractical in a complex environment because of the long learning time required by the agent. Therefore, guidelines are necessary in order to expedite the learning process in such environments, and imitation is one such guideline. Sakato, Ozeki, and Oka...
In the context of adaptive component-based systems, self-expression is the capability of changing the adaptation pattern at run-time when some changes occur in the system itself or in its environment. Even if functional requirements can be met without changing the adaptation pattern, the achievement of non-functional requirements, such as performance, can benefit from a change of adaptation pattern...
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...
Methodology for advanced design and modeling and some practical results of development of distributed mechatronic environment are presented based on robotic contact systems with technological adaptation. Some practical results and examples of 3D virtual models of such kind of mechatronic systems are suggested as well.
The performance of a model, which is trained with offline data, is highly relied on the conditions in which the system is working. When the working conditions change, the prediction accuracy of the model will be reduced significantly. To solve this problem, we propose an adaptive SVR modeling method based on vector-field-smoothed (VFS) algorithm. This method can adapt the model quickly to new working...
During the lifetime of a real world agent or robot, many changes unforeseen at design time can occur. Whether these are due to a change in environmental conditions or to alterations of the embodiment of the robot, flexibility and adaptation are essential qualities that can help it to keep operating in this new situation. This work is based on an information-theoretic approach and introduces an exploration...
Co-evolving a robotpsilas sensor morphology and control program increases the potential that it can effectively complete its tasks and provides a means for adapting to changes in the environment. In previous work, we presented a learning system where the angle, range, and type of sensors on a hexapod robot, along with the control program, were evolved. Although three sensor stimuli were detectable...
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