Crazyswarm: A large nano-quadcopter swarm

By James A. Preiss, Wolfgang Honig, G. Sukhatme, Nora Ayanian. IEEE International Conference on Robotics and Automation, 2017

450 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/da631e3b79ba97666fabb50ed65915d07c887966

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Radhika Nagpal

In Computer Networks and Communications

1. Florian Berlinger
2. Agoston E. Eiben
3. Radhika Nagpal
4. Tamás Nepusz
5. Tamás Vicsek
6. Melvin Gauci
7. Albert-László Barabási
8. Yang-Yu Liu

Citations in the corpus

• Implicit coordination for 3D underwater collective behaviors in a fish-inspired robot swarm (2021, methodology): “…(used at the 2018 Winter Olympics) and the Crazyswarm are centrally controlled by a single computer and depend heavily on the Global Positioning System (GPS) and motion capture, respectively ( 27 , 28 ), whereas the VIO-Swarm uses local visual inertial odometry (VIO) to determine position ( 29 ).”
• Optimized flocking of autonomous drones in confined environments (2018, background): “Autonomous drone swarms also appear in the scientific literature, using indoor motion capture–based (29, 30), outdoor Global Positioning System (GPS)–based (24, 31–33), or even vision-assisted (34, 35) navigation.”
• Swarm Robotic Behaviors and Current Applications (2020, methodology): “, accelerometer, gyroscope, magnetometer, and a high precision pressure sensor (Preiss et al., 2017).”