YoVDO

Understanding Human Behavior for Robotic Assistance and Collaboration

Offered By: Paul G. Allen School via YouTube

Tags

Robotics Courses Psychology Courses Machine Learning Courses Computer Vision Courses Cognitive Sciences Courses Human-Robot Interaction Courses Nonverbal Communication Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore a 58-minute lecture from the Fall 2019 Robotics Colloquium featuring Henny Admoni from Carnegie Mellon University. Delve into the world of human-robot collaboration and its potential to revolutionize work and daily life. Learn about the importance of robots recognizing human mental states, including goals, intentions, and assistance needs, through nonverbal cues like eye gaze and gestures. Discover how a multidisciplinary approach combining robotics, psychology, machine learning, and computer vision is crucial for developing effective collaborative robots. Examine Admoni's research on robots assisting humans with complex tasks, such as meal preparation, and how cognitive science techniques inform robot algorithms for improved human-robot interactions. Gain insights into Admoni's background, including her role as an Assistant Professor at Carnegie Mellon University's Robotics Institute and her research focus on natural human communication in human-robot partnerships. Originally recorded on 12/6/19, this closed-captioned lecture offers valuable knowledge for those interested in the future of robotics and human-machine collaboration.

Syllabus

Fall 2019 Robotics Colloquium: Henny Admoni (Carnegie Mellon University)


Taught by

Paul G. Allen School

Related Courses

Introduction to Artificial Intelligence
Stanford University via Udacity
Computer Vision: The Fundamentals
University of California, Berkeley via Coursera
Computational Photography
Georgia Institute of Technology via Coursera
Einführung in Computer Vision
Technische Universität München (Technical University of Munich) via Coursera
Introduction to Computer Vision
Georgia Institute of Technology via Udacity