Miscellaneous

[Airicist]

https://youtu.be/P85XU6YY6Xk

Core Magazine @ Gadget Show 2013 [Swarm Robots]

Published on Aug 12, 2014


[IEEE CSS Video Clip Contest 2014 Submission]
This video highlights the work on multi-agent robotics at the GRITSLab at the Georgia Institute of Technology. By drawing inspiration from the world around us, different ways of interacting with the robots are discussed, with control theory playing a key role for making the human-swarm interactions happen.

[Airicist]

https://youtu.be/TgQ6f0xFwbE

Control-Theoretic Swarm Joysticks

Published on Aug 12, 2014


[IEEE CSS Video Clip Contest 2014 Submission]
This video highlights the work on multi-agent robotics at the GRITSLab at the Georgia Institute of Technology. By drawing inspiration from the world around us, different ways of interacting with the robots are discussed, with control theory playing a key role for making the human-swarm interactions happen.

[Airicist]

https://youtu.be/8vIRxUIs7N0

Group genius: Why fish are smarter in swarms

Published on Feb 4, 2014


When animals swarm they exhibit a complex collective intelligence that could help us build robots, heal wounds and understand the brain
Read more:

"Mind meld: The genius of swarm thinking (https://www.newscientist.com/article/mg22129540-800-mind-meld-the-genius-of-swarm-thinking)"
When animals swarm they exhibit a complex collective intelligence that could help us build robots, heal wounds and understand the brain

January 29, 2014

[Airicist]

http://vimeo.com/75494206

MakerSwarm Robot Hive
September 26, 2013


This video shows an example of wiring up a Robot Hive member to the swarm. Controlling servos and alpha numeric displays is shown, as is getting a button press event from the hive.

[Airicist]

https://youtu.be/i3ernrkZ91E

Swarm robots cooperate with AR drone

Published on Oct 23, 2012


"Spatially Targeted Communication and Self-Assembly," by Nithin Mathews, Anders Lyhne Christensen, Rehan O'Grady, and Marco Dorigo, from Universite Libre de Bruxelles and Instituto Universitario de Lisboa, was presented at IROS 2012 in Vilamoura, Portugal.

[Airicist]

https://vimeo.com/70324772

ChIRP Box Pushing Demo


ChIRP robots performing a simple box pushing task, inspired by foraging ants. The objective of the experiment is to have a swarm of robots collectively push a box without using any communication.
The box is emitting IR-light that the robots can detect and therefore distinguish the box from other obstacles. It is too heavy for a single robot to push alone, meaning that the robots need to cooperate in order to push it. Each robot only knows that other robots and a box may be present, but has no notion of where they can be situated in the environment. Moreover no direct communication is allowed between the robots. The robots have to search for the box, and at the same time avoid other robots and obstacles they may encounter.
If the box is detected, the robot starts pushing for a predefined time. This time depends on how many neighbouring robots are assumed to be pushing the box. If a robot detects that it cannot move the box, it tries to reposition to another side of the box. Multiple robots pushing on the same side are thus more inclined to continue pushing instead of reposition to another side, and this will eventually converge enough robots pushing on the same side of the box, resulting in a force sufficient to move the box.
chirp.idi.ntnu.no

[Airicist]

https://vimeo.com/67492880

Vito Trianni - Swarm Cognition, from natural to artificial systems (and back)


Abstract: The seminar presents an approach to the study of cognition in collective, swarm-like systems (referred to as the "swarm cognition" approach).
This approach has two main objectives: on the one hand, the theoretical understanding of the mechanisms that support cognitive processing and behavioural optimality in animal swarms; on the other hand, the definition of an engineering methodology that provides formal methods and tools for the design of cognitive capabilities in distributed multi-robot systems. These two objectives are deeply intertwined. The theoretical understanding will support the definition of a suitable engineering methodology for cognitive systems through the identification of the basic mechanisms used in cognitive processing, which must be translated into formal methods and guidelines for engineering artificial systems (e.g., the interactions observed between bees during nest site selection can be distilled into design patterns leading to an optimal decision making process). Similarly, the requirements for a suitable engineering methodology can support the identification of general mechanisms used in cognitive processes (e.g., the need to provide robustness to an engineered system could point to more detailed models which could be tested against the biological system). I will present the studies of biological systems that constitute the background of the swarm cognition approach, and discuss the work-in-progress for the definition of an engineering methodology for distributed cognitive systems.

[Airicist]

TERMES Project (https://pr.ai/showthread.php?5397), Self-organizing Systems Research Group, Harvard University, Cambridge, Massachusetts, USA

[Airicist]

https://youtu.be/wWEkjMODnAU

Underwater Swarms

Published on Aug 5, 2015

[Airicist]

https://youtu.be/BeUT_AL6t4A

Swarm Robotics: Invasion of the Robot Ants

Published on Nov 12, 2013


Watch as a throng of tiny, self-organizing machines—flashing lights on, speakers playing vintage video game music—search, cluster, and disperse with a single command. We owe much of this groundbreaking technology—known as "swarm robotics"—to visionary engineer James McLurkin, named one of the country's top five robot designers by Time magazine. His machines perform striking organizational and teamwork tasks in a method with origins in the behavior of ants and bees, and with real-world application and stakes: his swarm can clear minefields, execute complex missions on Mars, and search the aftermath of natural disasters for survivors. Learn more from McLurkin and witness his mechanical colony in action.

[Airicist]

Swarms of drones (https://pr.ai/showthread.php?12454)

[Airicist]

https://youtu.be/stzQNjtDg0g

Controlling Robotic Swarms

Published on Dec 2, 2014

[Airicist]

https://youtu.be/qXpjX49N7Zo

Robot swarms: will they bomb us or save us?

Published on Sep 21, 2015


Swarms have existed for millions of years in nature and now they’re evolving into silicon.

[Airicist]

https://youtu.be/SkvpEfAPXn4

Robots with a mind of their own

Uploaded on Mar 13, 2008

[Airicist]

https://youtu.be/Ql5lCLJ0tE8

Green worms create a superorganism that becomes a giant seaweed

Published on Feb 24, 2016


These flatworms live off energy provided by the green algae they store in their tissues - allowing them to spend their lives sunbathing on sandy beaches

"Green worms create a superorganism that becomes a giant seaweed (https://www.newscientist.com/article/2078532-green-worms-create-a-superorganism-that-becomes-a-giant-seaweed)"
Zoologger is our weekly column highlighting extraordinary animals – and occasionally other organisms – from around the world

by Josh Gabbatiss
February 24, 2016

[Airicist]

https://youtu.be/5S0GUnHVQfI

Mysterious deep-sea swarm of crabs filmed off the coast of Panama

Published on Apr 12, 2016


Video captured off the coast of Panama shows a surprising underwater swarm of red crabs, spotted further south than ever before. Where are they headed?

Mysterious deep-sea swarm of thousands of crabs caught on camera (https://www.newscientist.com/article/2083974-mysterious-deep-sea-swarm-of-thousands-of-crabs-caught-on-camera)

[Airicist]

https://youtu.be/n_qRuHkD5lc

Flocking with fixed-wing robots at EPFL

Uploaded on Sep 26, 2011


Inexpensive and easy to use MAVs, developed by Severin Leven and Sensefly, are shown here to be able to flock in formations up to ten robots. The project, presented by Sabine Hauert from EPFL's Laboratory of Intelligent Systems, will be shown at the IROS 2011 annual meeting.

[Airicist]

https://youtu.be/8Ik7V_QH5wk

Zooids: Building Blocks for Swarm User Interfaces

Published on Oct 4, 2016


Zooids: Building Blocks for Swarm User Interfaces
Mathieu Le Goc, Lawrence H Kim, Ali Parsaei, Jean-Daniel Fekete, Pierre Dragicevic, Sean Follmer

UIST 2016: Proceedings of the 29th Annual ACM Symposium on User Interface Software & Technology

Abstract:
This paper introduces swarm user interfaces, a new class of human-computer interfaces comprised of many autonomous robots that handle both display and interaction. We describe the design of Zooids, an open-source open-hardware platform for developing tabletop swarm interfaces. The platform consists of a collection of custom-designed wheeled micro robots each 2.6 cm in diameter, a radio base-station, a high-speed DLP structured light projector for optical tracking, and a software framework for application development and control. \ We illustrate the potential of tabletop swarm user interfaces through a set of application scenarios developed with Zooids, and discuss general design considerations unique to swarm user interfaces.

Zooids: Building Blocks for Swarm User Interfaces (https://dl.acm.org/citation.cfm?doid=2984511.2984547)

[Airicist]

Article "How can swarm roboticists contribute to and benefit from the wisdom of other disciplines? (https://robohub.org/how-can-swarm-roboticists-contribute-to-and-benefit-from-the-wisdom-of-other-disciplines)"

by Chih-Chun Chen, Nathan Crilly
November 8, 2016

[Airicist]

OFFSET Envisions Swarm Capabilities for Small Urban Ground Units (https://pr.ai/showthread.php?16036), DARPA, Arlington, Virginia, USA

[Airicist]

https://youtu.be/T-uy4Sq1YDo

Fleets of Drones

Published on Mar 3, 2017


From swarm intelligence to highly-choreographed light shows, we take a look at how a collection of drones can behave in interesting and breathtaking ways.

[Airicist]

https://youtu.be/uAAYivTtOpQ

The coming robot swarms

Published on Apr 13, 2017

[Airicist]

https://youtu.be/IUI6OMbUzAU

Controlling robot swarms with augmented reality

Published on Apr 26, 2017

[Airicist]

https://youtu.be/TUxNRvqRltk

Human perception of swarm robot motion

Published on May 3, 2017


"Human Perception of Swarm Robot Motion (https://dl.acm.org/citation.cfm?doid=3027063.3053220)"
by Griffin Dietz, Jane L E, Peter Y Washington, Lawrence H Kim, Sean Follmer

CHI'17: ACM CHI Conference on Human Factors in Computing Systems
Late-Breaking Work

Abstract:
As robots become ubiquitous in our everyday environment, we start seeing them used in groups, rather than individually, to complete tasks. We present a study aimed to understand how different movement patterns impact humans' perceptions of groups of small tabletop robots. To understand this, we focus on the effects of changing the robots' speed, smoothness, and synchronization, on perceived valence, arousal, and dominance. We find that speed had the strongest correlation to these factors. With regard to human emotional response to the robots, we align with and build on prior work dealing with individual robots that correlates speed to valence and smoothness to arousal. In addition, participants noted an increase in positive affect in response to synchronized motion, though synchronization had no significant impact on measured perception. Based on our quantitative and qualitative results, we describe design implications for swarm robot motion.

[Airicist]

https://youtu.be/pmZZzIXIIsc

Quadcopters swarm safely in tight formation

Published on May 15, 2017


Georgia Institute of Technology researchers have created a team of free-flying robots that obeys the two rules of the air: don’t collide or undercut each other. They've given them virtual "top hats" to avoid flying underneath and messing up the airflow.

The research will be presented at the 2017 IEEE International Conference on Robotics and Automation (ICRA) May 29 – June 3 in Singapore.

[Airicist]

https://youtu.be/36jCUTWGBAo

Crazyswarm: A large nano-quadcopter swarm

Uploaded on Jun 2, 2017


“Crazyswarm: A Large Nano-Quadcopter Swarm,” by James A. Preiss, Wolfgang Honig, Gaurav S. Sukhatme, and Nora Ayanian from University of Southern California. Presented at 2017 IEEE International Conference on Robotics and Automation (ICRA) in Singapore.

[Airicist]

https://youtu.be/-3EXTNw5aw0

Thinking and acting swarmish: towards intuitive control of robotic swarms

Published on Aug 16, 2017

[Airicist]

https://youtu.be/nKMp5tyM_rs

Swarm Robotics podcast

Published on Aug 20, 2017

[Airicist]

Article "A language to design control algorithms for robot swarms (https://robohub.org/a-language-to-design-control-algorithms-for-robot-swarms)"

by Lenka Pitonakova
September 28, 2017

[Airicist]

https://youtu.be/q2yVbjSnmdc

Robots evenly distribution algorithm in action

Published on Oct 2, 2017

[Airicist]

https://youtu.be/xtaF8_kLeFY

Swarm robotics

Published on Oct 3, 2017


A 4th year BE and 3rd year BEng Tech project at Auckland University of Technology School of Engineering,Computing and Mathematical Sciences. Electrical and Electronic Engineering Department. The robots can dock and re-charge themselves.

[Airicist]

https://youtu.be/0bRocfcPhHU

What intelligent machines can learn from a school of fish | Radhika Nagpal (https://pr.ai/showthread.php?t=7165)

Published on Oct 6, 2017


Science fiction visions of the future show us AI built to replicate our way of thinking -- but what if we modeled it instead on the other kinds of intelligence found in nature? Robotics engineer Radhika Nagpal studies the collective intelligence displayed by insects and fish schools, seeking to understand their rules of engagement. In a visionary talk, she presents her work creating artificial collective power and previews a future where swarms of robots work together to build flood barriers, pollinate crops, monitor coral reefs and form constellations of satellites.

[Airicist]

https://youtu.be/rE-qvV13nHQ

Published on Oct 12, 2017


While people often think about swarms as simply being large collections of robots, swarms, in fact, have five defining characteristics: number, agent complexity, collective complexity, heterogeneity, and human-swarm interaction. DARPA's OFFensive Swarm-Enabled Tactics (OFFSET) program will explore these characteristics as it seeks to develop and demonstrate operationally relevant swarm tactics that could be used by groups of unmanned air and/or ground systems numbering more than 250 robots. These swarm tactics for large teams of unmanned assets would help improve force protection, firepower, precision effects, and intelligence, surveillance, and reconnaissance (ISR) capabilities.

[Airicist]

https://youtu.be/bEm-fXkLw7g

Morphogenesis in robot swarms

Published on Dec 19, 2018


Morphogenesis allows millions of cells to self-organize into intricate structures with a wide variety of functional shapes during embryonic development. This process emerges from local interactions of cells under the control of gene circuits that are identical in every cell, robust to intrinsic noise, and adaptable to changing environments. Constructing human technology with these properties presents an important opportunity in swarm robotic applications ranging from construction to exploration. Morphogenesis in nature may use two different approaches: hierarchical, top-down control or spontaneously self-organizing dynamics such as reaction-diffusion Turing patterns. Here, we provide a demonstration of purely self-organizing behaviors to create emergent morphologies in large
swarms of real robots. The robots achieve this collective organization without any self-localization and instead rely entirely on local interactions with neighbors. Results show swarms of 300 robots that self-construct organic and adaptable shapes that are robust to damage. This is a step toward the emergence of functional shape formation
in robot swarms following principles of self-organized morphogenetic engineering.

Read the paper:
Slavkov, I., Zapata D. C. et al., Science Robotics (2018)

Reprinted with permission from Slavkov, I., Zapata D. C. et al., Science Robotics (2018).

"Growing bio-inspired shapes with a 300-robot swarm (https://robohub.org/growing-bio-inspired-shapes-with-a-300-robot-swarm)"

by Sabine Hauert
December 19, 2018

[Airicist]

https://youtu.be/aXrljS7wBic

Particle robots

Published on Mar 20, 2019


Researchers from MIT, Columbia University, and elsewhere have developed computationally simple robots that connect in large groups to move around, transport objects, and complete other tasks.

"“Particle robot” works as a cluster of simple units (https://news.mit.edu/2019/particle-robot-cluster-simple-units-0320)"
Loosely connected disc-shaped “particles” can push and pull one another, moving en masse to transport objects.

by Rob Matheson
March 20, 2019

[Airicist]

https://youtu.be/miw80gBemcA

Make: Live - Swarm bots

Streamed live March 23, 2019


Radio controlled vehicles are a common target for makers, and cars like the Thunder Tumbler provide an affordable, accessible platform. Using Particle's new, mesh-ready hardware, we'll create a SwarmBot network of Tumblers that move in synchronized fashion!

[Airicist]

Article "The social animals that are inspiring new behaviours for robot swarms (https://theconversation.com/the-social-animals-that-are-inspiring-new-behaviours-for-robot-swarms-113584)"

by Edmund Hunt
March 27, 2019

[Airicist]

https://youtu.be/Ox-SNBW7TO0

Onboard evolution of understandable swarm behaviors

Published on Aug 23, 2019

"Onboard Evolution of Understandable Swarm Behaviors (https://onlinelibrary.wiley.com/doi/full/10.1002/aisy.201900031)"

by Simon Jones, Alan Winfield (https://pr.ai/showthread.php?t=10340), Sabine Hauert (https://pr.ai/showthread.php?t=13227), Matthew Studley (https://www.linkedin.com/in/matt-studley-2547875)
July 18, 2019

[Airicist]

https://youtu.be/W8PrTpI69nM

Eciton robotica: Design and Algorithms for an Adaptive Self-Assembling Soft Robot Collective

Mar 4, 2020


This video accompanies the paper of the same name published at ICRA 2020.

Inspired by the bridges and bivouacs formed by army ants, we designed a hardware system Eciton robotica, composed of soft, flexible robots that climb over and attach to each other to assemble structures. The robots use a simple local rule: they stop and become a “bridge” when stepped on. Robots in hardware know they are stepped on by sensing a vibration pulse. Using this local rule, robots in simulation are able to self-assemble structures that adapt to traffic levels and terrain.

ssr.seas.harvard.edu/ecitonswarm (https://ssr.seas.harvard.edu/ecitonswarm)

[Airicist]

https://youtu.be/pBrm9EQNfGs

SwarmRail: a novel overhead robot system for indoor transport and mobile manipulation (https://www.dlr.de/rm/en/desktopdefault.aspx/tabid-13938)

Jun 10, 2020


SwarmRail represents a novel solution to overhead manipulation from a mobile unit that drives in an above ground rail-structure. The concept is based on the combination of omnidirectional mobile platform and L-shaped rail profiles that form a through-going central gap. This gap makes possible mounting a robotic manipulator arm overhead at the underside of the mobile platform. Compared to existing solutions, SwarmRail enables continuous overhead manipulation while traversing rail
crossings. It also can be operated in a robot swarm, as it allows for concurrent operation of a group of mobile SwarmRail units inside a single rail network. Experiments on a first functional demonstrator confirm the functional capability of the concept. Potential fields of applications reach from industry over logistics to vertical farming.

[Airicist]

https://youtu.be/615LmMNBFJg

Collective worm and robot "blobs" protect individuals, swarm together (https://phys.org/news/2021-02-worm-robot-blobs-individuals-swarm.html)

Feb 11, 2021


Researchers at Georgia Tech are studying the collective behaviors of the California blackworm and applying the worm blob movement principles to swarm robotics.

Saad Bhamla (https://www.linkedin.com/in/saadbhamla)

bhamla.com (https://www.bhamla.com)

[Airicist]

https://youtu.be/cAXUKNGpMG4

Drone swarms avoid obstacles without collision (https://actu.epfl.ch/news/helping-drone-swarms-avoid-obstacles-without-hitti)

May 18, 2021


Engineers at EPFL have developed a predictive control model that allows swarms of drones to fly in cluttered environments quickly and safely. It works by enabling individual drones to predict their own behavior and that of their neighbors in the swarm.

Enrica Soria (https://www.linkedin.com/in/enrica-soria-05735b109)

"Watch a Drone Swarm Fly Through a Fake Forest Without Crashing (https://www.wired.com/story/watch-a-drone-swarm-fly-through-a-fake-forest-without-crashing)"
Each copter doesn’t just track where the others are. It constantly predicts where they’ll go.

by Max Levy (https://www.linkedin.com/in/levymax)
June 9, 2021

[Airicist]

https://youtu.be/hsLJShwjknI

Simple Robots, Smart Algorithms: Meet the BOBbots

May 3, 2021


Inspired by a theoretical model of particles moving around on a chessboard, new robot swarm research led by Georgia Tech shows that, as magnetic interactions increase, dispersed “dumb robots” can abruptly gather in large, compact clusters to accomplish complex tasks. Researchers report that these “BOBbots” (behaving, organizing, buzzing bots) are also capable of collectively clearing debris that is too heavy for one alone to move, thanks to a robust algorithm.

"Simple Robots, Smart Algorithms: Meet the BOBbots (https://cos.gatech.edu/news/simple-robots-smart-algorithms-meet-bobbots)"

April 29, 2021

[Airicist2]

https://youtu.be/OVPC2WaQ-5U

Loopy - a robot swarm or a single robot?

Jun 18, 2022


Loopy is a robotic swarm of 1- Degree of Freedom (DOF) agents (i.e., a closed-loop made of 36 Dynamixel servos). Each agent (servo) makes it's own local decisions based on interactions with its two neighbors.
In this video, Loopy is trying to go from an arbitrary initial shape to a goal shape (Flying WV).
We have more plans for Loopy...

yugu.faculty.wvu.edu (https://yugu.faculty.wvu.edu)

Playlist "Loopy (https://www.youtube.com/playlist?list=PLBZTHzLUXEzhvFhCGtT7pDLiRF-Sg5eS7)"

[Airicist2]

https://youtu.be/plrS-dbwXr8

Large scale interactive drone swarm management

Oct 19, 2022


Imagine being able to control a swarm of drones with just your hands or gestures.

In this video, we explore a future concept-of-operations for swarm management and how large groups of robots and drones will be able to interact and work together.

The system senses the operator’s intent and controls drone trajectories and swarm states such as take-off, animation sequences, drone camera controls, and landing in real-time.

State synchronization and inter-swarm communication is managed through a highly optimized distributed control network that is based on our novel zero-trust for robotics architecture.

This technology has many potential applications, including for entertainment and tasks such as search and rescue, inspection or agricultural management.

Additionally, interactive swarm management could also be used for security purposes, as it would allow a large number of drones to be deployed quickly and efficiently. While this technology is still in its early stages, it has great potential and could revolutionize the way we manage large groups of semi-autonomous vehicles.

If you have any questions or would like to learn more, please don’t hesitate to get in touch. We’d be happy to chat with you about this exciting technology and its potential applications. Thank you for watching!