Mobile Robotics: A Practical Introduction

Nehmzow, Ulrich

doi:10.1007/978-1-4471-3392-6

Cited by 60 publications

(26 citation statements)

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“…By using an embodiment, such as the NXT, the sensory input does not longer need to be simulated. The learning program receives its input directly through the attached sensors that react to the stimuli that are already available in the real world [6]. The learning system could, for example, try to learn from the light sensor that is mounted on the bottom of a robotic car.…”

Section: Embodied Intelligencementioning

confidence: 99%

Teaching Machine Learning to Design Students

Vlist

Westelaken

Bartneck

et al. 2008

Technologies for E-Learning and Digital Entertainment

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Abstract. Machine learning is a key technology to design and create intelligent systems, products, and related services. Like many other design departments, we are faced with the challenge to teach machine learning to design students, who often do not have an inherent affinity towards technology. We successfully used the Embodied Intelligence method to teach machine learning to our students. By embodying the learning system into the Lego Mindstorm NXT platform we provide the student with a tangible tool to understand and interact with a learning system. The resulting behavior of the tangible machines in combination with the positive associations with the Lego system motivated all the students. The students with less technology affinity successfully completed the course, while the students with more technology affinity excelled towards solving advanced problems. We believe that our experiences may inform and guide other teachers that intend to teach machine learning, or other computer science related topics, to design students.

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Section: Embodied Intelligencementioning

confidence: 99%

Teaching Machine Learning to Design Students

Vlist

Westelaken

Bartneck

et al. 2008

Technologies for E-Learning and Digital Entertainment

View full text Add to dashboard Cite

show abstract

“…[Ark98] Both of the above descriptions include the field of control theory, which is the mathe matical study of how to manipulate the param eters affecting the behavior of a system in order to produce an optimal outcome. to compare the actual status of a system Xt at time t with a desired system status Tt [Neh99]. The monitor returns the error between the actual system state and the desired system state which is defined as Cf = -Tt [Neh99].…”

Section: Yb Ern Eticsmentioning

confidence: 99%

“…to compare the actual status of a system Xt at time t with a desired system status Tt [Neh99]. The monitor returns the error between the actual system state and the desired system state which is defined as Cf = -Tt [Neh99]. The error is then used as an input signal to a controller module [Neh99].…”

Section: Yb Ern Eticsmentioning

confidence: 99%

“…The monitor returns the error between the actual system state and the desired system state which is defined as Cf = -Tt [Neh99]. The error is then used as an input signal to a controller module [Neh99]. The job of the controller is to minimize the error between the actual system state and the desired system state [Neh99].…”

Section: Yb Ern Eticsmentioning

confidence: 99%

“…The error is then used as an input signal to a controller module [Neh99]. The job of the controller is to minimize the error between the actual system state and the desired system state [Neh99]. Therefore, the controller will choose an action yt+k such th a t yt+k = f{^t) = f{xt -"p) at the next time step t+k [Neh99].…”

Section: Yb Ern Eticsmentioning

confidence: 99%

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