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Fast Robot Optimization and Simulation Toolkit (FROST)
The main features of ayonga/frost-dev are: Physics Simulation.
Projects with overlapping indexed features include: carla-simulator/carla — CARLA is an autonomous driving simulator and research environment designed for developing and validating self-driving… genesis-embodied-ai/genesis-world — Genesis World is an embodied AI simulation platform designed for training robotic agents through physics-based… dusty-nv/jetson-inference — jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU… bulletphysics/bullet3 — Bullet3 is a professional physics simulation engine designed for calculating rigid body, soft body, and collision… dartsim/dart — Research-focused C++23 physics engine for robotics, animation, and machine learning, with Python bindings. danielchappuis/reactphysics3d — Open source C++ physics engine library in 3D.
CARLA is an autonomous driving simulator and research environment designed for developing and validating self-driving software. It functions as an urban traffic simulator that generates realistic vehicle and pedestrian behavior and as a synthetic sensor data generator producing LiDAR, Radar, and camera data. The platform distinguishes itself through its deep integration with robotics frameworks, specifically providing native connectivity to ROS2 nodes for robotic control and data processing. It supports the training of driving models via imitation and reinforcement learning within a controlle
Genesis World is an embodied AI simulation platform designed for training robotic agents through physics-based interactions. It centers on a multi-physics simulation engine that integrates rigid body, particle, and finite element method dynamics, supported by a parallel simulation kernel compiler that translates Python functions into optimized GPU and CPU kernels. The platform features a photorealistic robot renderer that utilizes path-tracing and Gaussian Splatting to generate synthetic training data. It includes a domain randomization framework to vary lighting and physical parameters acros
jetson-inference is a set of libraries and tools for executing optimized deep learning models on embedded GPU hardware. Its primary purpose is to enable real-time computer vision and AI inference at the edge with low latency and high throughput. The project distinguishes itself through high-performance streaming analytics and the ability to execute concurrent AI pipelines on auto-grade silicon. It provides specialized support for multi-sensor stream processing, utilizing zero-copy data transport to load camera frames directly into GPU memory. The codebase covers a broad surface of capabiliti
Bullet3 is a professional physics simulation engine designed for calculating rigid body, soft body, and collision dynamics within 3D environments and robotics applications. It functions as a computational framework for determining complex geometric intersections and contact manifolds between objects in simulated space. The library distinguishes itself through a distributed rendering framework that scales heavy graphical workloads and scene generation tasks across large clusters of machines. This capability enables the production of massive datasets by distributing complex scene generation acr