RTMaps from Intempora is a component-based software development and execution environment which enables users to time-stamp, record, synchronize and play back data from various sensors and vehicle buses.
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To make the vision of autonomous driving a reality, it is important to always know the vehicle position within its environment at any given time. This is also required if no detailed map or satellite navigation is available. In these cases, SLAM algorithms offer a smart solution.
Indiana University – Purdue University Indianapolis (IUPUI) is researching ways to improve road transport safety for autonomous applications by analyzing the benefits of high-speed sensor data processing. RTMaps Embedded and NXP BlueBox are serving as the core real-time execution platform for embedded computing capabilities.
P3 has developed an Autonomous Data and Analytics Platform for Testing (ADAPT) to help customers evaluate the implementation of features for ADAS and autonomous driving. These include vision-based features and features for testing sensors as well as sensor configurations and algorithms. ADAPT leverages RTMaps software to verify and validate ADAS and algorithms for autonomous driving.
NAVYA relies on the multisensor development environment RTMaps from Intempora to develop complex functions for autonomous driving for the NAVYA ARMA, which is considered to be the first driverless production vehicle for regular traffic.
Data logging is one of the key stages in data-driven development in the ADAS/AD domain. Data must first be collected for training, and then data must be collected for validation and testing.
In July 2020, dSPACE acquired Intempora, a pioneer in the area of real-time development software. The two companies already had a long-standing strategic partnership. Through the acquisition, dSPACE now offers a unique and reliable end-to-end solution as well as optimized support for innovative development projects. In this interview, Nicolas du Lac, CEO of Intempora, explains the history of the company and how this closer cooperation will bring a unique value.
dSPACE and Intempora have built a cooperation that aims at providing a superior tool chain for developing advanced driver assistance systems and functions for highly automated driving. dSPACE will globally and exclusively distribute RTMaps by Intempora, an unparalleled software environment for multisensor applications.
This article gives you a brief overview of RTMaps and how it is seamlessly integrated into the dSPACE tool chain.
The training courses are dedicated to engineers involved in prototyping multisensor applications. You will learn how to acquire, process, synchronously record and play back sensor data in RTMaps. In the advanced course, you will gain hands-on experience in integrating algorithms using Python, C++, or Simulink® and learn how to use RTMaps in combination with dSPACE tool chain. You will also learn to develop and run applications on embedded platforms.
RTMaps Remote Studio – Develop algorithms directly on an embedded platform without having to connect a mouse, keyboard and monitor.
Multisensor applications play an essential role in many areas such as advanced driver assistance systems, autonomous driving, multimodal human-machine interfaces, robotics and aerospace.
Developing these types of applications in the lab or in vehicle requires capturing, synchronizing, and processing data in real time from multiple sensors such as cameras, lidars, radars, or GNSS receivers and interfacing with communication networks/buses, such as Ethernet (e.g., SOME/IP, DDS), CAN/CAN FD, FlexRay, or LIN. During the test and development phase, it is also essential to be able to record, visualize and play back time-correlated data. RTMaps (Real-Time Multisensor applications) from Intempora (www.intempora.com) is designed specifically for these use cases. It provides a modular development and run-time environment for x86- and ARM-based platforms supporting operating systems such as Microsoft Windows® and Linux.
With RTMaps, data is acquired asynchronously and each data sample is captured along with its time stamp at its own genuine pace. This ensures that all data is time-correlated. RTMaps’ unparalleled performance on multicore CPUs enables users to get the most out of their computing architectures and easily set up applications that handle multiple, high-bandwidth data streams, including real-time processing and data fusion. Sensor data can be recorded and played back synchronously for offline development and testing under reproducible conditions and in a faster-than-real-time mode.
RTMaps provides comprehensive component libraries for automotive sensors, buses and perception algorithms and it supports any type and quantity of sensors and actuators. Algorithms can be developed easily by means of block diagrams or by integrating own code using dedicated software development kits for C++ and Python. It is even possible to process data on multiple distributed platforms while preserving time coherency and synchronization of heterogeneous data streams.
RTMaps is tightly integrated in the dSPACE tool chain. For this, dSPACE provides an interface blockset designed specifically for dSPACE’s PC-based simulation platform VEOS and dSPACE real-time systems to exchange data with low latencies and synchronize clocks with RTMaps. In addition, dSPACE ControlDesk® can be connected to RTMaps via the ASAM XIL API, which lets users monitor and parameterize components that are implemented and processed in RTMaps.
|Supported sensors, communication buses and protocols||
|Supported algorithms for developing functions for autonomus driving||
|Supported operating systems and platforms||
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