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Example Project: A final project template for DeepRob

Anthony Opipari
University of Michigan
Huijie Zhang
University of Michigan
Jiyue Zhu
University of Michigan
Karthik Desingh
University of Minnesota
Odest Chadwicke Jenkins
University of Michigan
Teaser Figure

Abstract

This course covers the necessary background of neural-network-based deep learning for robot perception – building on advancements in computer vision that enable robots to physically manipulate objects. During the first part of this course, students will learn to implement, train and debug their own neural networks. During the second part of this course, students will explore recent emerging topics in deep learning for robot perception and manipulation. This exploration will include analysis of research publications in the area, building up to reproducing one of these publications for implementation as a final course project.

Results

Visual results are great for project webpages; exciting results can captivate an audience and convey dense information efficiently. We suggest including images, figures, animations, and videos on your webpage. For example, static images can be displayed as shown below:

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Project Video

You can display a video with your model’s results by either uploading to youtube, then copying your video’s <iframe> source as shown below. Alternatively if your video files are small, we can host them directly on the DeepRob server.

Citation

If you found our work helpful, consider citing us with the following BibTeX reference:

@article{opipari2023deeprob,
  title = {Example Project: A final project template for DeepRob},
  author = {Opipari, Anthony and Zhang, Huijie and Zhu, Jiyue and Desingh, Karthik and Jenkins, Odest Chadwicke},
  year = {2023}
}

Be sure to update this reference to include your team’s author information for correct attribution!

Contact

If you have any questions, feel free to contact Anthony Opipari and Prof. Chad Jenkins.