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Neuromorphic computing is a promising solution for reducing the size, weight and power of mobile embedded systems. In this paper, we introduce a realization of such a system by creating the first closed-loop battery-powered communication system between an IBM Neurosynaptic System (IBM TrueNorth chip) and an autonomous Android-Based Robotics platform. Using this system, we constructed a dataset of...
This is an extended abstract describing the doctoral research on mentioned topic which is only to discuss the research in Ph.D symposium at INMIC 2014 conference. Proposed research and material presented in this extended abstract was also presented in the doctoral consortium at IMTIC 2013 at MUET, Pakistan and WEC 2013 conference at NUST Islamabad, Pakistan. This article is not intended to be published...
Object recognition plays an important role in robotics, since objects/tools first have to be identified in the scene before they can be manipulated/used. The performance of object recognition largely depends on the training dataset. Usually such training sets are gathered manually by a human operator, a tedious procedure, which ultimately limits the size of the dataset. One reason for manual selection...
As improvements in per-transistor speed and energy efficiency diminish, radical departures from conventional approaches are becoming critical to improving the performance and energy efficiency of general-purpose processors. We propose a solution—from circuit to compiler—that enables general-purpose use of limited-precision, analog hardware to accelerate “approximable” code—code that can tolerate imprecise...
Visual navigation is an important research field in robotics because of the low cost and the high performance that is usually achieved by visual navigation systems. Pixel classification as a road pixel or a non-road pixel is a task that can be well performed by Artificial Neural Networks. In the case of real-time instances of the image classification problem, as when applied to autonomous vehicles...
BECCA (a Brain-Emulating Cognition and Control Architecture software package) was developed in order to perform general reinforcement learning, that is, to enable unmodeled embodied systems operating in unstructured environments to perform unfamiliar tasks. It accomplishes this through automatic paired feature creation and reinforcement learning algorithms. This paper describes an implementation of...
We present an integrated vision and robotic system that plays, and learns to play, simple physically-instantiated board games that are variants of TIC TAC TOE and HEXA-PAWN. We employ novel custom vision and robotic hardware designed specifically for this learning task. The game rules can be parametrically specified. Two independent computational agents alternate playing the two opponents with the...
As a synthetic training procedure and method, science and technology research project can directly affect the training quality of our university students. Always aimed at resolving the real problem, research projects can implement valid summing-up and improvement of the knowledge learned in class. In this paper, we analyzed the phenomenon and status of university students. Then, the requirement and...
Robotics plays a very important role in medical engineering. Thus, it is necessary for students of medical engineering to acquire knowledge on robotics during their studies. Besides teaching expertise, a robotics project provides many possibilities for students to acquire additional qualifications for their career. Robotics is an inter- and cross-disciplinary field and hence holds a unique role among...
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