Showing 4 open source projects for "linux gpib support"

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  • 1
    PX4 Autopilot

    PX4 Autopilot

    PX4 Autopilot Software

    ...It is also the leading research platform for drones and has been successfully applied to underwater vehicles and boats. PX4 provides a standard to deliver drone hardware support and software stack, allowing an ecosystem to build and maintain hardware and software in a scalable way. Drone development is complicated, and how to get started can be daunting and hard to navigate. These tutorials and resources provide a walkthrough of the basics of PX4. PX4 is highly portable, OS-independent and supports Linux, NuttX and MacOS out of the box. ...
    Downloads: 37 This Week
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  • 2
    CARLA Simulator

    CARLA Simulator

    Open-source simulator for autonomous driving research.

    CARLA has been developed from the ground up to support development, training, and validation of autonomous driving systems. In addition to open-source code and protocols, CARLA provides open digital assets (urban layouts, buildings, vehicles) that were created for this purpose and can be used freely. The simulation platform supports flexible specification of sensor suites, environmental conditions, full control of all static and dynamic actors, maps generation and much more. Multiple clients...
    Downloads: 11 This Week
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  • 3
    Alpamayo 1

    Alpamayo 1

    Bridging Reasoning and Action Prediction

    Alpamayo 1 is a pre-trained reasoning model developed by NVIDIA to support research and development in autonomous driving systems. It combines perception, reasoning, and action prediction into a unified architecture, enabling it to interpret complex driving scenarios and generate trajectory plans. The model is designed as a foundational component rather than a complete driving stack, allowing developers to build custom autonomous vehicle applications on top of it. It incorporates...
    Downloads: 0 This Week
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  • 4
    BEVFormer

    BEVFormer

    Implementation of BEVFormer, a camera-only framework

    3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV...
    Downloads: 0 This Week
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