HCI Deep Dives is your go-to podcast for exploring the latest trends, research, and innovations in Human Computer Interaction (HCI). Auto-generated using the latest publications in the field, each episode dives into in-depth discussions on topics like wearable computing, augmented perception, cognitive augmentation, and digitalized emotions. Whether you’re a researcher, practitioner, or just curious about the intersection of technology and human senses, this podcast offers thought-provoking insights and ideas to keep you at the forefront of HCI.
All content for HCI Deep Dives is the property of Kai Kunze and is served directly from their servers
with no modification, redirects, or rehosting. The podcast is not affiliated with or endorsed by Podjoint in any way.
HCI Deep Dives is your go-to podcast for exploring the latest trends, research, and innovations in Human Computer Interaction (HCI). Auto-generated using the latest publications in the field, each episode dives into in-depth discussions on topics like wearable computing, augmented perception, cognitive augmentation, and digitalized emotions. Whether you’re a researcher, practitioner, or just curious about the intersection of technology and human senses, this podcast offers thought-provoking insights and ideas to keep you at the forefront of HCI.
DIS 2025 ELEGNT: Expressive and Functional Movement Design for Non-anthropomorphic Robot
HCI Deep Dives
12 minutes 12 seconds
8 months ago
DIS 2025 ELEGNT: Expressive and Functional Movement Design for Non-anthropomorphic Robot
Hu, Yuhan, Peide Huang, Mouli Sivapurapu, and Jian Zhang. "ELEGNT: Expressive and Functional Movement Design for Non-anthropomorphic Robot." arXiv preprint arXiv:2501.12493(2025).
https://arxiv.org/abs/2501.12493
Nonverbal behaviors such as posture, gestures, and gaze are essential for conveying internal states, both consciously and unconsciously, in human interaction. For robots to interact more naturally with humans, robot movement design should likewise integrate expressive qualities—such as intention, attention, and emotions—alongside traditional functional considerations like task fulfillment, spatial constraints, and time efficiency. In this paper, we present the design and prototyping of a lamp-like robot that explores the interplay between functional and expressive objectives in movement design. Using a research-through-design methodology, we document the hardware design process, define expressive movement primitives, and outline a set of interaction scenario storyboards. We propose a framework that incorporates both functional and expressive utilities during movement generation, and implement the robot behavior sequences in different function- and social-oriented tasks. Through a user study comparing expression-driven versus function-driven movements across six task scenarios, our findings indicate that expression-driven movements significantly enhance user engagement and perceived robot qualities. This effect is especially pronounced in social-oriented tasks.
HCI Deep Dives
HCI Deep Dives is your go-to podcast for exploring the latest trends, research, and innovations in Human Computer Interaction (HCI). Auto-generated using the latest publications in the field, each episode dives into in-depth discussions on topics like wearable computing, augmented perception, cognitive augmentation, and digitalized emotions. Whether you’re a researcher, practitioner, or just curious about the intersection of technology and human senses, this podcast offers thought-provoking insights and ideas to keep you at the forefront of HCI.