Showing 8 open source projects for "project-open"

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    Build Agents and Models on One Platform

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  • 1
    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. ...
    Downloads: 7 This Week
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  • 2
    highway-env

    highway-env

    A minimalist environment for decision-making in autonomous driving

    HighwayEnv is an OpenAI Gym-compatible environment focused on autonomous driving scenarios. It provides flexible simulations for testing decision-making algorithms in highway, intersection, and merging traffic situations.
    Downloads: 1 This Week
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  • 3
    AWS IoT FleetWise Edge

    AWS IoT FleetWise Edge

    AWS IoT FleetWise Edge Agent

    Easily collect, transform, and transfer vehicle data to the cloud in near-real-time. AWS IoT FleetWise makes it easy and cost-effective for automakers to collect, transform, and transfer vehicle data to the cloud in near-real-time and use it to build applications with analytics and machine learning that improve vehicle quality, safety, and autonomy. Train autonomous vehicles (AVs) and advanced driver assistance systems (ADAS) with camera data collected from a fleet of production vehicles....
    Downloads: 1 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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    Cut Data Warehouse Costs by 54%

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  • 5
    Coach

    Coach

    Enables easy experimentation with state of the art algorithms

    Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments...
    Downloads: 0 This Week
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  • 6
    Software Infrastructure for Stanford's Autonomous Vehicles
    Downloads: 2 This Week
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  • 7
    This project intends to develop a system to control the vehicles over a wireless network. Each vehicle contains embedded software that interfaces with a set of sensors and actuators that allow the vehicle to navigate, to communicate with roadside sensors,
    Downloads: 0 This Week
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  • 8
    Alpamayo 2 Super

    Alpamayo 2 Super

    Open VLA model for autonomous driving reasoning and planning

    Alpamayo2-Super is NVIDIA’s flagship open reasoning Vision-Language-Action (VLA) model for autonomous vehicle development, designed to accelerate Level 4 robotaxi and autonomous driving systems. Built on the NVIDIA Cosmos platform, it enables vehicles to perceive, reason, plan, and generate driving actions using human-like decision making rather than relying solely on predefined rules.
    Downloads: 0 This Week
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