The US company has introduced the ‘Guide n580’ single 9 x 6 x 6cm box unit for a broad range of uses, including agriculture, robotics and autonomous vehicles, claiming that it will yield precise navigation in GNSS-denied areas such as tall cities, tunnels and multi-layer roads, as well as during GNSS outages.

A company spokesman explains: ‘The blend of inertial and satellite navigation capabilities provided by the HGuide n580 is especially important where precision is required in demanding environments - for example, autonomous cars traveling in cities, where our technology can extend the accuracy and performance of navigational systems while keeping passengers safe.’

GNSS signals used include all civil signals transmitted by GPS, GLONASS, BeiDou, Galileo and India’s IRNSS. Augmentation used can include SBAS, post-processed or real-time kinematic (PPK/RTK) modes. It can use single or dual antennas.

Claimed accuracies (95%) with GNSS available include 1.2m in both H & V using SBAS, with heading to 0.1º and pitch/roll to 0.03º. Further errors (RMS) introduced with GNSS denied are claimed after 30 seconds to be H 1m, V 0.5m and heading 0.08º.

Honeywell

Today’s autonomous vehicles require detailed 3-D maps, but a novel system enables navigation with just GPS and sensors.

Companies such as Google only test their autonomous vehicles in major cities - where they have spent countless hours meticulously recording the exact 3-D positions of the likes of lanes, curbs, ramps and stop-signs.

The Director of the US MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) explains: 'The cars use these maps to know where they are and what to do in the presence of new obstacles like pedestrians and other cars. The need for dense 3-D maps limits the places where self-driving cars can operate.'

So, if one lives along the millions of miles of roads that are unpaved, unlit or unreliably marked, one cannot use autonomous driving. Such roads are often much more complicated to map, and get a lot less traffic - so companies have little incentive to develop 3-D maps for them.

In a first step to overcome the problem, CSAIL have developed 'MapLite' - a framework that allows self-driving cars to drive on roads that they have never been on before; and without 3-D maps.

MapLite combines basic GPS data that can be found on Google Maps with a series of sensors that observe the road conditions. Combined, these two elements permitted the team to autonomously drive on multiple unpaved country roads, reliably detecting the road more than 100 ft ahead. In collaboration with the Toyota Research Institute, the researchers used a Toyota Prius car that they fitted with a range of light detection and ranging (LIDAR) and inertial measurement unit (IMU) sensors.

A leading author of a related paper on the system states: 'The reason this kind of ‘map-less’ approach hasn’t really been done before is because it is generally much harder to reach the same accuracy and reliability as with detailed maps. A system like this that can navigate just with on-board sensors shows the potential of self-driving cars being able to actually handle roads beyond the small number that tech companies have mapped.'

More at: http://news.mit.edu/2018/self-driving-cars-for-country-roads-mit-csail-0507