08 Jul 2021
When gas leaks occur – for example in warehouses, environmental emergencies, or search and rescue operations – it is very important to be able to locate the source of the leak in order to take fast and effective countermeasures. This is usually done using animals, which is very costly and puts human and animal lives in danger.
Chiara Ercolani is a Ph.D. student at the Distributed Intelligent Systems and Algorithms Laboratory (DISAL) at École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. Chiara and her team believe that using robots to detect gas leaks is the best way to save lives.
One of the team’s most recent projects involved 3D gas source localization using a micro aerial vehicle (drone).
In this experiment, they used a Crazyflie flying robot (drone) with a VOC sensor to sense gas particles in the air. Their goals were to:
The experiment was conducted in a wind tunnel facility (16x4x2) m3 with laminarized wind flow of adjustable speed. An electric pump was used to disperse a mixture of ethanol and air in the wind tunnel to create the gas plume.
A view of the wind tunnel with gas source, flying drone, and Motion Analysis Kestral 1300 cameras.
Gas dispersion is a 3D phenomenon, so to be effective in 3D gas source localization, the team needed to use platforms capable of 3D motion tracking.
The team experimented with sensor location, performance under various environmental conditions, and two localization strategies. The full results can be viewed in this short video summary.
For the purposes of this article, we will focus on the third aspect of the experiment, namely determining what effect each of the following localization methods would have on the outcome of the gas source localization:
While UWB localization is easier to deploy and cheaper, this experiment makes it clear that using a motion capture system offers better performance under all tested environmental conditions. The drone’s movements are clearly much cleaner and smoother than those obtained when a UWB system is used for localization. As a result, the drone is faster and more efficient.
These results show that MCS localization is more accurate than UWB localization. We also see that the drone’s movement is much more efficient when the MCS is used.
Our team has been working with the DISAL lab for many years, so we were pleased when Chiara got in touch to purchase a second motion capture system from us. They now have 13 Kestrel 1300 cameras and use Cortex to process their data.
Here’s what Chiara has to say about working with Motion Analysis:
“When we needed to purchase a second motion capture system, Motion Analysis was our first choice. Not only is the system great to use, but the sales team is always very helpful. They helped us to envision the system setup within the wind tunnel and we are in regular contact with them for tips and advice.”
To learn more about the work that Chiara’s team is doing, please visit https://www.epfl.ch/labs/disal/research/3dodorsensing/
To learn more about the motion capture system and the powerful Cortex software, please visit our solution overview page.
To request a demo, please get in touch here: https://www.motionanalysis.com/request-a-demo/