Sensing technologies for electronic situational awareness has seen lots of progress, driven by all the attention currently being given to autonomous vehicles (AV). The advances in materials, topology, and processes have resulted in a new generation of sensor systems, which in turn enable the creation of new, cost-effective solutions.
This explosion in targeted automated solutions has been enabled by the significant reduction in cost in advanced subsystems. The need for accurate, reliable, and efficient systems to support AV location and movement has thrown the spotlight on a core infrastructure technology, the inertial measurement unit (IMU).
Formerly the realm of the military and other “cost-is-no-object” application spaces like aerospace, IMUs are now available to be used in the most cost-sensitive applications. One example is the European VineRobot project, which is developing a novel unmanned agricultural robot equipped with several non-invasive sensing technologies to monitor vineyards. Until now, it has required direct human action to determine critical vineyard yield aspects like vegetative growth, water status, and grape composition
Multiple issues are involved in developing a robot that can operate in the real world, and they’re exacerbated by application-specific issues. In the case of a vineyard robot, both technical and business challenges need to be addressed.
Vineyards differ in a significant way from most other agricultural situations. The most notable aspect is terrain, as most vineyards in Europe are on hillsides and other, often steep, landscapes. This creates several challenges to an agricultural robot for vineyards, as tire profile, vehicle suspension, and motor torque become very important when driving off the vertical.
Another serious issue arising from operating (alternating up and downslope) on a steep incline is the higher importance on vehicle presence. What angle are the tires to the face? How steeply and in what direction is the vehicle tilted? There are lots of considerations when going from a 2D to a 3D surface for navigation purposes. Things get stickier quickly when you add issues like vehicle orientation for proper sensor operation.