CAD Seminar Series: Intention Recognition and Trajectory Tracking in Human-Robot Interaction Using D

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When:
October 9, 2024
2:30 p.m. to 3:30 p.m.
Where:
Event category: Seminar
Virtual

Speaker:  Sara Masoud, Ph.D.

Assistant Professor, Industrial and Systems Engineering WSU
 
Time: Wednesday, October 9, from 2:30 to 3:30 pm
 
Place: Online 
 
 
Title: Intention Recognition and Trajectory Tracking in Human-Robot Interaction Using Deep Learning and VR
 
Abstract
Recognizing intentions and tracking trajectories in Human-Robot Interaction (HRI) is crucial for enabling robots to anticipate and respond to human actions effectively. This study investigates the use of deep learning techniques for classifying and tracking human intentions and locations in HRI, with data gathered from Virtual Reality (VR) environments. By utilizing VR, a controlled and immersive setting is established, allowing for precise monitoring and recording of human behaviors. Ensemble deep learning models, particularly Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and Transformers, were trained on this rich dataset to recognize and predict human intentions and track their trajectories with high accuracy. While CNN and CNN-LSTM models delivered high accuracy, they faced challenges in correctly identifying certain intentions. In contrast, the CNN-Transformer model outperformed the others, achieving higher precision, recall, and F1-scores in classification, along with strong performance in trajectory tracking. This approach highlights the potential for enhancing HRI by equipping robots with the ability to understand and respond to human intentions in real-time, fostering more intuitive and effective human-robot collaboration. The experimental results underscore the promise of deep learning in advancing intention recognition in HRI.
 
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CAD Seminar Series: Advancing Knowledge, Innovation, and Collaboration in Computation, AI, and Data Science (CAD)
 
The CAD Seminar Series is a dedicated platform for advancing knowledge, fostering innovation, and promoting collaboration across the fields of Computation, Artificial Intelligence, and Data Science. This series brings together leading experts, researchers, and professionals to explore the latest developments, tackle emerging challenges, and drive forward-thinking solutions at the convergence of these critical disciplines.
 
Objectives:
 
• Advance Knowledge: Share cutting-edge research and insights that push the boundaries of what is known in CAD.
• Foster Innovation: Encourage the development of novel ideas and solutions through interdisciplinary dialogue and creative thinking.
• Promote Collaboration: Unite expertise across disciplines and build bridges between academia, industry, and government to address complex problems and create opportunities for joint ventures.
Schedule: The seminars will be held on a weekly basis (unless otherwise noted) throughout the academic year. For Fall 2024, the seminars are tentatively scheduled for Wednesdays from 2:30 PM to 3:30 PM, and will be available both in-person at 1146 FAB and online. Each seminar will spotlight a particular topic, providing an in-depth exploration and fostering lively discussions. 
 
Target Audience: The CAD Seminar Series is designed for a diverse audience, including faculty, researchers, students, and professionals in Computation, AI, Data Science, and related fields. It serves as a forum for exchanging ideas, networking, and contributing to the growth of these rapidly evolving areas. We highly recommend in-person attendance to enhance engagement and networking opportunities with speakers and fellow participants.
 
Call for Participation: We welcome contributions from researchers, practitioners, and students. Whether presenting your work, participating in discussions, or attending as a learner, your involvement is crucial to the success of this collaborative initiative. 

Contact

Rohini Kumar
rohini.kumar@wayne.edu

Cost

Free
October 2024
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