Marine Litter Mapping

DSC_1110A project I have been thinking about and wanting to do for a very long time is to build a fully autonomous litter collecting robot. This driven by the annoyance I always feel when passing a nearby park, littered with Twix wrappers, coke cans, and the like. Challenging? Very much so. Impossible? No. You just have to pick your constraints.

I wish this was the blog post I would explain how I built the robot and how it all works, including snazzy youtube video. However, while I have already started down the path I still have a long (but fun!) way to go. In particular my Orangutans have been keeping me busy and will continue to do so for a while. I have also changed my professional affiliation but that’s a topic for the next post. It does explain though why my interest was piqued when Peter Kohler (GIS expert from SESexplore, and Fishackathon fame) told me about his project to raise awareness around marine litter. And that is the real topic of this post.

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Where’s Susi? Airborne Orangutan Tracking with Python and React.js

camp-from-above-smallTL;DR: You are faced with a few thousand hectares of rainforest that you know harbours one or more orangutans that you need to track down. Where, how, and why do you start looking?

Background

About a year ago I was doing a lot of drone related work and was presented with the following problem: Would it be possible to use a drone to fly above the Bornean jungle and search for tagged orangutans?

To understand the motivation behind the question we need some background.

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Landmine or Coke Can: Deep Learning with GPR Data

Time Slices5_Grid9One of the projects that has taken up a lot of my time the past few months is that of a UAV (drone) based Ground Penetrating Radar (GPR) system. There are a number of applications for this but the one we have been focussing on initially is landmine and UXO clearance. The elements that make up such a system are quite broad. Ranging from sensor design, UAV integration, positioning, terrain following to data analysis. As with many drone projects most of the attention tends to go to the hardware and the flying. While that is certainly important and I have been working on those elements too, the whole system is only as good as the quality and interpretability of the data you get back. That is key. With this post I’ll aim to give a brief summary of the work I have been leading on this front.

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MSF Canada Drone Day

DSC00266I recently had the honour of attending the MSF Canada AGM in Montreal to join Ivan Gayton and Stephen Mather (from Open DroneMap fame) run a drone day for the MSF logisticians. The aim being to show the realm of the possible with current drone technology as well as touch on future trends and ethical considerations.

A second agenda we had was to promote the democratisation of drone technology to enable crowd sourced imagery collection as part of the Missing Maps initiative. 2015-06-12 14.57.27More specifically, the goal is to bring drone technology down to a level where it can be built, maintained, and operated safely, responsibly, and independently by a local high school in South Sudan, the local University of Lubumbashi, or similar. 

The full (draft) concept note behind this can be found here.

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