A Survey of research in Deep Learning for Robotics for Undergraduate research interns

TL;DR

This paper surveys research internship projects that apply deep learning techniques to robotic problems, providing a concise overview for students interested in robotics and AI.

Contribution

It compiles and summarizes recent research projects in deep learning for robotics, specifically targeting undergraduate interns and aspiring students.

Findings

Highlights diverse applications of deep learning in robotics

Provides insights into research trends and challenges

Serves as a resource for internship aspirants

Abstract

Over the last several years, use cases for robotics based solutions have diversified from factory floors to domestic applications. In parallel, Deep Learning approaches are replacing traditional techniques in Computer Vision, Natural Language Processing, Speech processing, etc. and are delivering robust results. Our goal is to survey a number of research internship projects in the broad area of 'Deep Learning as applied to Robotics' and present a concise view for the benefit of aspiring student interns. In this paper, we survey the research work done by Robotic Institute Summer Scholars (RISS), CMU. We particularly focus on papers that use deep learning to solve core robotic problems and also robotic solutions. We trust this would be useful particularly for internship aspirants for the Robotics Institute, CMU