Search Results for "suicide-linux"
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Showing 13 open source projects for "suicide-linux"
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PX4 Autopilot
PX4 Autopilot Software
...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. The PX4 User Guide explains how to assemble supported vehicles and fly drones with PX4. See the forum and chat if you need help! -
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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... -
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sunnypilot
Open source driver assistance system
sunnypilot is an open-source driver-assistance system derived from comma.ai’s openpilot and designed primarily for comma 3 and 3X hardware. It supports hundreds of vehicle makes and models while modifying how steering, acceleration, braking, and cruise assistance behave. Its Modular Assistive Driving System provides more flexible engagement behavior than the upstream project. Neural-network lateral control, automatic lane changes, and configurable driving models expand steering... -
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openpilot
Open source driver assistance system
openpilot is an open-source driver assistance system designed to improve upon the existing driver assistance of most modern cars today. openpilot gives you Tesla Autopilot-like functionality with functions like Adaptive Cruise Control (ACC), Automated Lane Centering (ALC), Forward Collision Warning (FCW) and Lane Departure Warning (LDW). All these with just a push of a button. openpilot also includes a camera-based driver monitoring feature that alerts distracted and asleep drivers while it... -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
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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. -
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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... -
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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.... -
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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... -
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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... -
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road-scene-understanding
A dataset for road scene understanding.
Autonomous driving is gaining increasing attention in the computer vision research community, as vision based scene understanding is key to self-driving cars. In this web page, we make image datasets public for the purpose of furthering research in scene understanding. -
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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,
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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. The model processes multi-camera video, navigation signals, and driving context to produce driving...
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