Developing Applications for Industrial Vehicles, Autonomous Agriculture, and Smart Farming

• Develop applications faster using a graphical block-based approach and a framework tailored to multisensor applications
• Benefit from a component library and easily connect your algorithms to a variety of sensors as well as bus and communication interfaces
• Use only one tool for all development tasks and focus on your actual work while having the software work for you

Task

Multisensor applications for intelligent assistance systems and automated driving are the topics of the day not only in the automotive industry, but also in many other sectors, such as construction, mining, agriculture or even smart farming. Leading manufacturers and suppliers work on tractors and construction site machinery with autonomous functions, and harvesting machines or AI-empowered robots for smart farming.

Challenge

Even though the applications are completely different in each domain, they all rely on the same principles. Asynchronous data streams from different sensor types like camera, radar, or lidar and GNSS data have to be gathered in a time-correlated manner, efficiently connected to perception algorithms, and smartly synchronized to enable tasks like reliable data fusion, localization and mapping, path planning, and further advanced algorithms, including control functions.

Solution

You can either integrate sensors and develop everything by your own while struggling with different tools and confusing middleware that lacks features and standard support. Or you can opt for one perfectly tailored, long-established development framework for real-time multisensor applications (RTMaps) to bring your applications to the market faster. RTMaps is a generic tool and an integration champion that enables easy connection of sensors, vehicle, and communication buses with your algorithm. It lets you concentrate on the actual development and test tasks while letting the software work for you, with proper time-correlated data communication. RTMaps runs efficiently on the most common embedded platforms using Windows, Linux or QNC, and can be easily adapted to your needs. A large component library that comes with RTMaps by default provides convenient blocks for integrating sensors, communication interfaces, data recording, replay and visualization to support all major steps of application development in a single tool.