Bridging Disciplines for a New Era in Physical AI

Physical AI is extending models from the digital world into performing tasks in the real world. Robots and autonomous cars are common examples of physical AI agents. In this workshop, we aim to go beyond containing physical AI in those agents and ask what if all objects and materials we interact with were intelligent? We aim to form an understanding of the opportunities and challenges of extending agents to include objects and materials that can adapt to users needs, i.e., change shape, firmness, color, tactile properties, etc. This broad vision, which is challenging to achieve, is related to many active research areas, e.g., programmable matter, modular robotics, soft robotics, smart materials, shape-changing interfaces, or radical atoms, and has homes in many disciplines, incl. mechanical engineering, robotics, material science, computer science. Many new approaches are being developed in the individual disciplines that together might be the start of a new era for what we like to call extended physical AI. In this workshop, we bring perspectives from these different disciplines together to exchange new approaches to longstanding challenges (e.g., actuation, computational design, fabrication, control), exchange tacit knowledge, discuss visions for future applications, map the new grand challenges, and inspire the next generation of physical AI research.

Authors

Institutions

Publication Details

Published
2024-10-11
DOI
https://doi.org/10.1145/3672539.3686704
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Bridging Disciplines for a New Era in Physical AI

Carmel Majidi, Lining Yao, Alexandra Ion, Amir H. Alavi
Modular Robots and Swarm Intelligence
article

Bridging Disciplines for a New Era in Physical AI

Carmel Majidi, Lining Yao, Alexandra Ion, Amir H. Alavi
article en

Abstract

Physical AI is extending models from the digital world into performing tasks in the real world. Robots and autonomous cars are common examples of physical AI agents. In this workshop, we aim to go beyond containing physical AI in those agents and ask what if all objects and materials we interact with were intelligent? We aim to form an understanding of the opportunities and challenges of extending agents to include objects and materials that can adapt to users needs, i.e., change shape, firmness, color, tactile properties, etc. This broad vision, which is challenging to achieve, is related to many active research areas, e.g., programmable matter, modular robotics, soft robotics, smart materials, shape-changing interfaces, or radical atoms, and has homes in many disciplines, incl. mechanical engineering, robotics, material science, computer science. Many new approaches are being developed in the individual disciplines that together might be the start of a new era for what we like to call extended physical AI. In this workshop, we bring perspectives from these different disciplines together to exchange new approaches to longstanding challenges (e.g., actuation, computational design, fabrication, control), exchange tacit knowledge, discuss visions for future applications, map the new grand challenges, and inspire the next generation of physical AI research.

University of Pittsburgh (US), Carnegie Mellon University (US), University of California, Berkeley (US)
Openalex Percentile: Top 83%
Modular Robots and Swarm Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.