Abhishek Narula

dblp:176/0748 · DBLP profile ↗
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2ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Computing education · 100%
Artificial intelligence
1 paper
Robot navigation and mapping · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computing education › robotics education
educational robotics platform
0.812024
MBot: A Modular Ecosystem for Scalable Robotics Education · ICRA 2024
Computing education
robotics education
0.812024
MBot: A Modular Ecosystem for Scalable Robotics Education · ICRA 2024
Robotics › Robot navigation and mapping
mobile robot navigation
0.212024
MBot: A Modular Ecosystem for Scalable Robotics Education · ICRA 2024
YearPublicationVenuePosition
2024 MBot: A Modular Ecosystem for Scalable Robotics Education
abstract
The Michigan Robotics MBot is a low-cost mobile robot platform that has been used to train over 1,400 students in autonomous navigation since 2014 at the University of Michigan and our collaborating colleges. The MBot platform was designed to meet the needs of teaching robotics at scale to match the growth of robotics as a field and an academic discipline. Transformative advancements in robot navigation over the past decades have led to a significant demand for skilled roboticists across industry and academia. This demand has sparked a need for robotics courses in higher education, spanning all levels of undergraduate and graduate experiences. Incorporating real robot platforms into such courses and curricula is effective for conveying the unique challenges of programming embodied agents in real-world environments and sparking student interest. However, teaching with real robots remains challenging due to the cost of hardware and the development effort involved in adapting existing hardware for a new course. In this paper, we describe the design and evolution of the MBot platform, and the underlying principals of scalability and flexibility which are keys to its success.
Peter Gaskell, Jana Pavlasek, Tom Gao, Abhishek Narula, Stanley Lewis 0001, Odest Chadwicke Jenkins
ICRA4
2016 Crafting Mechatronic Percussion with Everyday Materials
abstract
We present a kit comprising cardboard mechanical components and a custom printed circuit board, designed to support novices in building computational percussive instruments with everyday materials. We set three design criteria: accessibility, adaptability, and expressivity. We conducted two workshops with experts and novices to assess the usability of our kit and observe the variety of constructions that users make. The kit enabled both experts and novices to build working instruments and to explore creative experimentation with different materials and objects.
HyunJoo Oh 0001, Jiffer Harriman, Abhishek Narula, Mark D. Gross, Michael Eisenberg, Sherry Hsi
TEI3