95. SLAM Robotics

 
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This weeks post sets out to briefly explain one of the most exciting and/or frightening advances (depending on how you look at it) taking place in the geospatial world.

 
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It's fair to say that most geospatialists chose their field because they dreamed of working with cutting edge technology. Today, however working 'with' geospatial technology now means working 'alongside' geospatial technology in the form of robots.

 
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Simultaneous localization and mapping (SLAM) is a system of robotic mapping and navigation which was pioneered in the early 1990's when researchers developed complex algorithms to overcome the age old problem of 'spatial uncertainty'. Today, SLAM is becoming a mainstream technology which can be found in the Unmanned Aerial Vehicle or 'Drone' systems which are now being developed by household tech companies such as Google, Apple, Amazon as well as fast changing traditional automotive and industrial tech companies.

 
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SLAM is a form of geospatial artificial intelligence which uses Lidar and sensor technology to scan and ‘learn’ about its surroundings, to detect obstacles and to devise optimal navigational routes. Among other applications, Naturally, SLAM underpins the predictive decision-making systems of driverless cars. The technology's enormous data collection capabilities can be aggregated and processed with live data from fixed sensors, GPS systems, Wifi signals, and even live data collected by other SLAM systems. Realtime 4D urban mapping is now a reality thanks to SLAM.

Needless to say, SLAM is going to revolutionise many industries, most notably precision-farming, mining, indoor surveillance and navigation, emergency services and above and below ground utilities management. It quickly removes the spatial uncertainty (i.e. 'where') element from navigating new places and in doing so will allow humans to explore previously hard-to-map spaces - terrestrial, marine and planetary.

 
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Naturally, SLAM will be a cause for concern among many professions which are focused on survey and mapping. It may, on the one hand, be combined with augmented reality technology in order to enhance human activity or, alternatively, it may be used to completely remove the need for certain professions. A SLAM devices doesn’t command a paycheque, it doesn’t get bored by tedious work, it knows when to recharge itself and, unlike humans on occasion, it knows when to ‘slam’ on the brakes.

For better or worse, SLAM is here to stay. The most important thing for geospatialists is to become aware of their new robotic colleagues.