Interface (matter)
Related papers: 20
About
An interface, in the context of robotics and AI, is the boundary or connecting layer through which two distinct systems — most commonly a human and a machine — exchange information, commands, and feedback. Interfaces can be physical, such as wearable electronics, exoskeletons, and prosthetic limbs; neural, such as brain-computer interfaces (BCIs) that decode electrical signals from the brain to control robotic devices; or software-based, enabling operators to command autonomous systems through visual displays or teleoperation controls. In robotics, interfaces are fundamental to enabling humans to direct robots, receive sensory feedback, and collaborate effectively with automated systems. Brain-machine interfaces, for example, allow paralyzed individuals to control robotic arms or wheelchairs through neural signals alone, while flexible skin-mounted sensors capture physiological data to drive wearable rehabilitative devices. Interfaces matter because they determine the bandwidth, naturalness, and reliability of human-robot interaction. A well-designed interface reduces cognitive load, enhances system safety, and expands what humans and robots can accomplish together — making them essential in medical rehabilitation, assistive technology, teleoperation, and human-robot teaming.
Top Researchers
Top Cited Papers
Intelligence without representation
Rodney A. Brooks
Citations: 4701 • 1991
Reach and grasp by people with tetraplegia using a neurally controlled robotic arm
Leigh R. Hochberg, Daniel Bacher, Beata Jarosiewicz, Nicolas Y. Masse, John D. Simeral, Jörn Vogel, Sami Haddadin, Jie Liu, Sydney S. Cash, Patrick van der Smagt, John P. Donoghue
Citations: 2730 • 2012
Lab-on-Skin: A Review of Flexible and Stretchable Electronics for Wearable Health Monitoring
Yuhao Liu, Matt Pharr, Giovanni A. Salvatore
Citations: 1661 • 2017
The Open Motion Planning Library
Ioan A. Şucan, Mark Moll, Lydia E. Kavraki
Citations: 1600 • 2012
Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans
Jonathan R. Wolpaw, Dennis J. McFarland
Citations: 1516 • 2004
Interactive evolutionary computation: fusion of the capabilities of EC optimization and human evaluation
Hideyuki Takagi
Citations: 1325 • 2001
Myoelectric control systems—A survey
Mohammadreza Asghari Oskoei, Huosheng Hu
Citations: 1238 • 2007
An Integrated Brain-Machine Interface Platform With Thousands of Channels
Elon Musk
Citations: 1055 • 2019
GraspIt!
Andrew Miller, Peter K. Allen
Citations: 1028 • 2004
Upper-Limb Powered Exoskeleton Design
Joel C. Perry, Jacob Rosén, Stephen P. Burns
Citations: 1001 • 2007
Toward sociable robots
Cynthia Breazeal
Citations: 992 • 2003
Principles of Animal Communication
Mark E. Laidre
Citations: 987 • 2012
State of the Art and Future Directions for Lower Limb Robotic Exoskeletons
Aaron J. Young, Daniel P. Ferris
Citations: 875 • 2016
A critical review of interfaces with the peripheral nervous system for the control of neuroprostheses and hybrid bionic systems
Xavier Navarro, Thilo B. Krueger, Natalia Lago, Silvestro Micera, Thomas Stieglitz, Paolo Dario
Citations: 841 • 2005
Noninvasive Brain-Actuated Control of a Mobile Robot by Human EEG
José del R. Millán, F. Renkens, J. Mouriño, Wulfram Gerstner
Citations: 739 • 2004
Brain-Computer Interfaces in Medicine
Jerry J. Shih, Dean J. Krusienski, Jonathan R. Wolpaw
Citations: 711 • 2012
A high-performance brain–computer interface
Gopal Santhanam, Stephen I. Ryu, Byron M. Yu, Afsheen Afshar, Krishna V. Shenoy
Citations: 707 • 2006
PX4: A node-based multithreaded open source robotics framework for deeply embedded platforms
Lorenz Meier, Dominik Honegger, Marc Pollefeys
Citations: 697 • 2015
Active tactile exploration using a brain–machine–brain interface
Joseph E. O’Doherty, Mikhail Lebedev, Peter J. Ifft, Katie Zhuang, Solaiman Shokur, Hannes Bleuler, Miguel A. L. Nicolelis
Citations: 634 • 2011
Human Performance Issues and User Interface Design for Teleoperated Robots
Jessie Y. C. Chen, Ellen C. Haas
Citations: 633 • 2007