Robohub.org
 

Finding outdoor odor sources using particle filters


by
05 April 2011



share this:

Robots with smell could be used to find sources of toxic gas, search for drugs, locate survivors under rubble or hidden mines. Robots have an advantage over sniffer dogs since they can enter dangerous areas and could potentially be deployed rapidly and at lower costs.

Most of the work on olfaction robots is done in controlled laboratory environments. Instead, Li et al. are looking at how robots can localize odor sources in outdoor environments with changing wind that can be turbulent and strong. To do this, they’ve developed a novel algorithm based on particle filters that tracks the location of the odor source over time.

Experiments were done using a two-wheeled robot equipped with a gas sensor, an anemometer (for wind measurements) and an electronic compass. The robot was placed in an outdoor 10 m × 10 m area and was asked to search for a humidifier containing liquid ethanol (odor source). To find the gas plume, the robot would perform spirals. As soon as gas was sensed, the robot followed a plume-tracing strategy to collect more information about the odor source. The videos below show the robot behavior (top) and the particle filter algorithm used (bottom).

Results show that the particle filter method is suitable for challenging outdoor odor source localization and that it outperforms Bayesian-inference-based methods.




Sabine Hauert is President of Robohub and Associate Professor at the Bristol Robotics Laboratory
Sabine Hauert is President of Robohub and Associate Professor at the Bristol Robotics Laboratory





Related posts :



Robot Talk Episode 112 – Getting creative with robotics, with Vali Lalioti

  07 Mar 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Vali Lalioti from the University of the Arts London about how art, culture and robotics interact.

Robot Talk Episode 111 – Robots for climate action, with Patrick Meier

  28 Feb 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Patrick Meier from the Climate Robotics Network about how robots can help scale action on climate change.

Robot Talk Episode 110 – Designing ethical robots, with Catherine Menon

  21 Feb 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Catherine Menon from the University of Hertfordshire about designing home assistance robots with ethics in mind.

Robot Talk Episode 109 – Building robots at home, with Dan Nicholson

  14 Feb 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Dan Nicholson from MakerForge.tech about creating open source robotics projects you can do at home.

Robot Talk Episode 108 – Giving robots the sense of touch, with Anuradha Ranasinghe

  07 Feb 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Anuradha Ranasinghe from Liverpool Hope University about haptic sensors for wearable tech and robotics.

Robot Talk Episode 107 – Animal-inspired robot movement, with Robert Siddall

  31 Jan 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Robert Siddall from the University of Surrey about novel robot designs inspired by the way real animals move.

Robot Talk Episode 106 – The future of intelligent systems, with Didem Gurdur Broo

  24 Jan 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Didem Gurdur Broo from Uppsala University about how to shape the future of robotics, autonomous vehicles, and industrial automation.

Robot Talk Episode 105 – Working with robots in industry, with Gianmarco Pisanelli 

  17 Jan 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Gianmarco Pisanelli from the Advanced Manufacturing Research Centre about how to promote the safe and intuitive use of robots in manufacturing.





Robohub is supported by:




Would you like to learn how to tell impactful stories about your robot or AI system?


scicomm
training the next generation of science communicators in robotics & AI


©2024 - Association for the Understanding of Artificial Intelligence


 












©2021 - ROBOTS Association