Laboratory of Intelligent Systems (LIS), bio-inspired artificial intelligence, autonomous robotic systems, Lausanne, Switzerland

[Airicist]

Website - lis.epfl.ch (https://lis.epfl.ch)

youtube.com/EPFLLIS (https://www.youtube.com/EPFLLIS)

Director - Dario Floreano (https://pr.ai/showthread.php?7171)

Projects:

drone with feathers (https://pr.ai/showthread.php?16046)

sensory-motor tissues for soft robots (https://pr.ai/showthread.php?11930)

Gimball (https://pr.ai/showthread.php?6434), spherical helicopter

folding drone (https://pr.ai/showthread.php?11249)

Airburr (https://pr.ai/showthread.php?2014), flying robot

Happy Holidays (https://pr.ai/showthread.php?9272)

DALER (https://pr.ai/showthread.php?10170) (Deployable Air-Land Exploration Robot)

RoboGen (https://pr.ai/showthread.php?8067), software/hardware platform for evolutionary robotics

[Airicist]

https://youtu.be/Y6Qt2X7UBIk

Acoustic Source Localization of Emergency Signals from Micro Air Vehicles

Published on Dec 10, 2013


In search and rescue missions, Micro Air Vehicles (MAV's) can assist rescuers to faster locate victims inside a large search area and to coordinate their efforts. Acoustic signals play an important role in outdoor rescue operations. Emergency whistles, as found on most aircraft life vests, are commonly carried by people engaging in outdoor activities, and are also used by rescue teams, as they allow to signal reliably over long distances and far beyond visibility. For a MAV involved in such missions, the ability to locate the source of a distress sound signal, such as an emergency whistle blown by a person in need of help, is therefore significantly important and would allow the localization of victims and rescuers during night time, through foliage and in adverse conditions such as dust, fog and smoke.
In this work we present a sound source localization system for a MAV to locate narrow-band sound sources on the ground, such as the sound of a whistle or personal alarm.

Basiri, M., Schill, F., Lima, P. U., & Floreano, D. (2012, October). Robust acoustic source localization of emergency signals from Micro Air Vehicles. In Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on (pp. 4737-4742). IEEE.

[Airicist]

https://youtu.be/sBo3jb3YPQo

A Flying Robot Controlled by Artificial Muscle

Published on Oct 21, 2014


The air vehicle shown in the video is consisted of actuators that are capable of antagonistic actuation. The actuators are composed of dielectric elastomer actuator (DEA), which is often called as artificial muscle. Thanks to the compliance of the DEA, the actuator is capable of passive folding and is resistant to external shocks and overloads. We integrated the device in the aircraft, which illustrated high performance of the actuator.

This work has been done as a collaboration work between the Microsystems for Space Technologies Laboratory (LMTS) and the Laboratory of Intelligent Systems (LIS) at the EPFL.

Article "New soft ‘antagonistic’ actuator enables robots to fold (https://robohub.org/new-soft-antagonistic-actuator-enables-robots-to-fold)"

by Linda Seward, NCCR
November 3, 2014

[Airicist]

https://youtu.be/6zsuDVMSf3o

On-Board Relative Bearing Estimation for Teams of Drones Using Sound (https://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7403916&filter%3DAND%28p_IS_Number%3A7419970%29)

Published on Mar 24, 2016


In a team of autonomous drones, individual knowledge about the relative location of teammates is essential. Existing relative positioning solutions for teams of small drones mostly rely on external systems such as motion tracking cameras or GPS satellites that might not always be accessible. In this letter, we describe an onboard solution to measure the 3-D relative direction between drones using sound as the main source of information. First, we describe a method to measure the directions of other robots from perceiving their engine sounds in the absence of self-engine noise. We then extend the method to use active acoustic signaling to obtain the relative directions in the presence of self-engine noise, to increase the detection range, and to discriminate the identity of robots. Methods are evaluated in real world experiments and a fully autonomous leader-following behavior is illustrated with two drones using the proposed system.

[Airicist]

https://youtu.be/rvijnNm2Djw

A drone for last-centimeter delivery

Published on Sep 11, 2017


A new drone developed at EPFL uses cutting-edge technology to deliver parcels weighing up to 500 grams. The device will never get stuck in traffic, it’s programmed to avoid obstacles, and it can reach destinations on steep or uneven terrain. Its protective cage and foldable design mean that it can be carried around in a backpack and used in total safety.

[Airicist2]

https://youtu.be/ARuuxTFpuHI

Robotic Elytra: insect-inspired protective wings for resilient and multi-modal drones

Nov 13, 2021


Winged drones that fly in close proximity to obstacles or that are capable of aerial and terrestrial locomotion can benefit from protective systems that prevent damage to delicate aerial structures. Existing protective solutions focus on multi-copter drones and consist of adding structures, such as cages, mechanisms and instruments that add weight and drag. Here we describe a protective strategy for winged drones that mitigates the added weight and drag by means of increased lift generation and stall delay at high angles of attack. The proposed structure is inspired by the wing system found in beetles and consists of adding an additional set of retractable wings, named elytra, which can rapidly encapsulate the main folding wings when protection is needed.

Publication reference:
Robotic Elytra: Insect-inspired Protective Wings for Resilient and Multi-modal Drones
Charalampos Vourtsis, William Stewart, and Dario Floreano
IEEE Robotics and Automation Letters

Laboratory of Intelligent Systems (LIS)
École Polytechnique Fédérale de Lausanne (EPFL)
CH-1015 Switzerland