For a better experience on, enable JavaScript in your browser. Thank you!

RTMaps – Real-time Multisensor Applications

Development Environment for Multisensor Applications (ADAS, robotics, …)

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. 

  • RTMaps Among Finalists for AutoSensAwards

    RTMaps has been selected as a finalist for the AutoSensAwards in the "Most Innovative Autonomous Driving Platform" category sponsored by NXP.

    Read more


  • Where Am I? – Environment recognition using SLAM algorithms

    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.

    Read more

  • Algorithms for Autonomous Driving

    The multisensor development environment RTMaps provides a range of algorithms for developing functions for autonomous driving.

    Read more

  • Speed is Key to Safety – Developing algorithms for autonomous driving

    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.

    Read more

  • Sensor-Based Driving – P3 develops features for ADAS and autonomous driving

    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.

    Read more

  • RTMaps Used to Develop Functions for Autonomous Driving for a Shuttle Bus

    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.

    Read more

  • Rising to Multisensor Challenges

    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.

    Read more

  • RTMaps Training

    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.

    Read more

Application Areas

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 kinds of applications in the lab or in the vehicle typically requires capturing, synchronizing and processing data in real time from various sensors such as cameras, laser scanners, radars or GNSS receivers and interfacing with communication networks, such as CAN/CAN FD, LIN or Ethernet. 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 ( 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. 

Key Benefits

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.

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.  

Integration in the dSPACE Tool Chain

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.

Functionality Description
  • Developing, testing, validating and benchmarking processing algorithms and data fusion algorithms
  • 2-D & 3-D visualization
  • Data time-stamping, latency measurement, downstream resynchronization
  • Datalogging and real-time data playback for offline development and validation
  • Graphical programming by means of block diagrams and easy integration of C++, Python and Simulink code
  • Optimized, multithread run-time engine and dedicated real-time capabilities
  • Data processing and data synchronization on multiple distributed platforms
  • RTMaps Studio with large module libraries for graphical development
  • RTMaps Remote Studio (an additional RTMaps Remote Studio license is required) to directly develop applications on embedded platforms using a PC
  • RTMaps Runtime Engine for embedded deployment and customized HMIs
  • Record and play back measurement data in ADTF DAT-file format
Supported sensors, communication buses and protocols
  • Cameras (GigE Vision, USB 2.0, USB 3.0, FireWire, analog, Camera Link, HDR, ... from Point Grey, IDS, Basler, AVT, NIT, ...)
  • Stereo-vision heads
  • Laser scanners (IBEO, Velodyne, SICK, Hokuyo, Quanergy, Ouster)
  • Radars (Delphi, Autocruise, Continental, ...)
  • Time-of-flight sensors (LeddarTech)
  • CAN/CAN FD, LIN (Peak, Kvaser, Vector Informatik, .dbc file decoder)
  • GPS, IMUs (SBG Systems, OxTS, Xsens, VectorNav, IXSEA, Phidgets, ...)
  • Communication (TCP & UDP, DDS, ASAM XIL API, ...)
  • Analog/digital I/O (Data Translation, Phidgets, Audio, ...)
  • Eye trackers (Pertech, faceLAB, SmartEye, SMI, The Eye Tribe, ...) and biometrics (BIOPAC, Becker Meditec, ...)
  • Motion capturing (Kinect, Xtion, Vicon, ...)
  • The complete list of available components is provided under:
    Support for additional components on request.
Supported algorithms for developing functions for autonomus driving
  • Open Source Computer Vision Library (OpenCV) for CPU/GPU-based image processing
  • Support for NVIDIA® DriveWorks for the DRIVE PX2 platform
  • Augmented LiDAR 3D SLAM provided by Dibotics via Partners Components Store
Supported operating systems and platforms
  • Windows®, Linux, Embedded Linux, QNX
  • x86, x86_64, ARM, MicroAutoBox Embedded SPU, AUTERA, Renesas HAD Solution Kit, NXP BlueBox, NVIDIA® DRIVE™ PX 2
Targeted applications
  • Advanced driving assistance systems (ADAS)
  • Autonomous vehicles
  • Mobile robotics
  • Data recording
  • Advanced multimodal HMIs

More Information Related Topics Contact Information