Event (particle physics)
Related papers: 20
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In particle physics and robotics/AI, an **event** refers to a discrete, instantaneous occurrence that triggers a response or computation — distinct from continuous, time-sampled data streams. In physics, an event marks a particle collision or interaction; in robotics and AI systems, the concept generalizes to any meaningful state change that drives processing. Event-based paradigms appear across multiple domains: event cameras (bio-inspired sensors that asynchronously report per-pixel brightness changes rather than capturing fixed-rate frames), discrete-event simulation frameworks for multi-agent systems, event-triggered control laws that update only when system conditions cross a threshold, and spiking neural network accelerators that process sparse, asynchronous signals. This asynchronous, data-driven approach contrasts sharply with periodic sampling, offering significant advantages in latency, energy efficiency, and bandwidth. In robotics, event-driven architectures enable faster sensor processing, more responsive control in dynamic environments, and scalable multi-agent coordination. They matter because they align computation with what actually changes in the world, reducing wasted processing and enabling real-time performance in applications ranging from visual odometry and corner detection to exoskeleton control and manufacturing supervision.
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Top Cited Papers
Event-Based Vision: A Survey
Citations: 2007 • 2020
MASON: A Multiagent Simulation Environment
Sean Luke, Claudio Cioffi‐Revilla, Liviu Panait, Keith Sullivan, Gabriel Balan
Citations: 1007 • 2005
Event-Based Vision: A Survey
Guillermo Gallego, Tobi Delbrück, Garrick Orchard, Chiara Bartolozzi, Brian Taba, Andrea Censi, Stefan Leutenegger, Andrew J. Davison, Jörg Conradt, Kostas Daniilidis, Davide Scaramuzza
Citations: 633 • 2020
The event-camera dataset and simulator: Event-based data for pose estimation, visual odometry, and SLAM
Citations: 562 • 2017
Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems
Citations: 448 • 2019
probabilistic robotics
Timo Oksanen, J. Tiusanen, Jari Kostamo
Citations: 420 • 2009
Secure Cooperative Event-Triggered Control of Linear Multiagent Systems Under DoS Attacks
Zhi Feng, Guoqiang Hu
Citations: 385 • 2019
A survey on recent advances in distributed sampled-data cooperative control of multi-agent systems
Xiaohua Ge, Qing‐Long Han, Derui Ding, Xian‐Ming Zhang, Boda Ning
Citations: 383 • 2017
Minitaur, an Event-Driven FPGA-Based Spiking Network Accelerator
Daniel Neil, Shih‐Chii Liu
Citations: 256 • 2014
DERVISH An Office-Navigating Robot
Illah Nourbakhsh, Rob Powers, Stan Birchfield
Citations: 248 • 1995
Max-Margin Early Event Detectors
Minh Hoai, Fernando De la Torre
Citations: 223 • 2013
Functional reactive programming from first principles
Zhanyong Wan, Paul Hudak
Citations: 211 • 2000
Low-latency visual odometry using event-based feature tracks
Beat Kueng, Elias Mueggler, Guillermo Gallego, Davide Scaramuzza
Citations: 197 • 2016
Learning the semantics of object–action relations by observation
Eren Erdal Aksoy, Alexey Abramov, Johannes Dörr, KeJun Ning, Babette Dellen, Florentin Wörgötter
Citations: 180 • 2011
Multi-robot area patrol under frequency constraints
Yehuda Elmaliach, Noa Agmon, Gal A. Kaminka
Citations: 179 • 2009
DEVS representation of dynamical systems: event-based intelligent control
Bernard P. Zeigler
Citations: 170 • 1989
Event-based feature tracking with probabilistic data association
Alex Zihao Zhu, Nikolay Atanasov, Kostas Daniilidis
Citations: 168 • 2017
Fast event-based Harris corner detection exploiting the advantages of event-driven cameras
Valentina Vasco, Arren Glover, Chiara Bartolozzi
Citations: 167 • 2016
The distributed simulation of multiagent systems
Brian Logan, Georgios Theodoropoulos
Citations: 161 • 2001
Optimal Subtask Allocation for Human and Robot Collaboration Within Hybrid Assembly System
Fei Chen, Kosuke Sekiyama, Ferdinando Cannella, Toshio Fukuda
Citations: 157 • 2013