Projects sharing features with Drake

CVXPY is a Python-embedded domain-specific language for modeling and solving convex optimization problems using natural mathematical syntax. It is built on a disciplined convex programming framework that automatically enforces convexity rules, ensuring that problems formulated by the user are valid for convex solvers. The project also functions as a multi-solver optimization interface, abstracting away backend details and dispatching problems to specialized solvers like ECOS, SCS, and Gurobi without manual configuration. Beyond standard convex optimization, CVXPY extends its reach to geometri

PythonRobotics is a comprehensive collection of modular robotics algorithms and educational simulations designed for autonomous navigation, state estimation, and motion control. The project provides a library of standalone implementations for path planning, localization, mapping, and kinematics, serving as a resource for researchers and students to experiment with foundational and advanced robotic theories. The project distinguishes itself through an algorithm-centric design where each module functions as an isolated script, allowing for independent testing and clear pedagogical demonstration

Optim.jl is a numerical optimization library for the Julia programming language, providing a comprehensive framework for minimizing or maximizing univariate and multivariate functions. It offers a suite of tools for solving both constrained and unconstrained mathematical problems, utilizing a variety of gradient-based, derivative-free, and stochastic search methods. The library distinguishes itself through a modular architecture that leverages language-level multiple dispatch to automatically select efficient solvers based on input data types and objective function properties. It supports com

Webots is a physics-based robot simulator and development environment used for modeling, programming, and testing the behavior of robots in a simulated 3D physical world. It serves as a virtual prototyping tool to verify mechanical and electronic systems through the creation of virtual robot models and control logic. The platform enables a full robotics simulation workflow, including the development of robot controllers and the programming of autonomous agent behaviors. It focuses on physical system modeling to represent the mechanical properties of hardware and simulate real-world interactio

Unitree RL Gym is an integrated software framework designed for the simulation, training, and deployment of motion control policies for legged robotic platforms. It provides a comprehensive environment for developing locomotion strategies for quadruped and humanoid robots by leveraging reinforcement learning algorithms within high-fidelity physics-based simulations. The platform distinguishes itself by offering an end-to-end workflow that bridges the gap between virtual training and physical execution. It includes specialized tools for mapping raw sensor data into normalized state-space obser

This project is a numerical computing library designed for scientific and engineering mathematical operations. It functions as a comprehensive linear algebra framework, a statistical analysis library, and a toolkit for mathematical optimization and numerical integration. The library is distinguished by its provider-based native acceleration, which allows managed code to be swapped for platform-native binary libraries to increase the performance of computationally intensive routines. It also supports a hybrid approach to matrix storage, implementing separate strategies for dense and sparse mat

Newton is a GPU-accelerated physics engine and robotics simulation platform designed for high-performance modeling of rigid bodies and complex articulations. It functions as a differentiable physics engine, calculating gradients to enable mathematical optimization and machine learning. The platform is distinguished by its ability to execute multiple parallel physics worlds on a single GPU, which accelerates data collection for reinforcement learning. It also supports the simulation of deformable bodies, such as cloth and cables, using particle-based methods and multi-physics coupling. Newton

Isaac Lab is an open-source framework for training robot policies in physically simulated environments, supporting both single-agent and multi-agent reinforcement learning. It is built on an Omniverse-PhysX simulation backend that models rigid bodies, articulated systems, deformable objects, and sensors, and provides a task-based environment configuration system where each training environment is defined as a modular class specifying observation spaces, action spaces, reward functions, and termination conditions. The framework distinguishes itself through an RL-library abstraction layer that

This project is a comprehensive software framework for autonomous robot navigation, providing a collection of algorithms for path planning, motion control, and trajectory generation. It serves as a toolkit for implementing and researching navigation logic, enabling the calculation of collision-free routes and the execution of precise movement commands for autonomous mobile agents. The library distinguishes itself by integrating both global pathfinding and real-time reactive control strategies. It supports diverse planning methodologies, including graph-based heuristic searches and sampling-ba

Habitat-sim is a high-performance 3D simulation platform designed for training and benchmarking embodied AI agents within photorealistic indoor and outdoor environments. It serves as a simulator for AI and robotics, providing a system for generating synthetic data and simulating physical interactions. The project is distinguished by a native C++ core that enables high-throughput simulation and a rendering pipeline using physically based rendering and baked global illumination. It features a navigation system based on pre-computed navigation meshes to ensure collision-free traversal and a rigi

dlib is a C++ machine learning toolkit and data analysis framework. It provides a collection of algorithms and utilities for building predictive modeling applications and performing statistical analysis on large datasets within native C++ environments. The project functions as a binding library that wraps low-level C++ machine learning algorithms into high-level Python scripting interfaces. This allows for the integration of high-performance native implementations with Python for machine learning development. The framework covers the implementation of predictive models, the execution of mach

Legged Gym is a high-performance simulation platform and toolkit engineered for training autonomous robotic agents in complex, physics-based environments. It provides a comprehensive framework for developing legged locomotion control policies, enabling robots to learn movement strategies for navigating uneven terrain and managing physical disturbances through reinforcement learning. The platform distinguishes itself by utilizing hardware-accelerated physics and headless execution to maximize computational throughput during training. It incorporates a domain randomization pipeline that injects

This project is a comprehensive library and framework for autonomous mobile robot navigation, providing a suite of geometric, heuristic, and optimization-based algorithms. It enables robots to calculate collision-free global paths and generate smooth, kinematically feasible local trajectories within complex environments. The system is built on a modular plugin architecture that allows developers to integrate and configure custom motion planning algorithms directly into the Robot Operating System. By utilizing a layered spatial representation, the framework aggregates heterogeneous sensor data

JoltPhysics is a high-performance C++ physics engine designed for multi-threaded simulation of 3D rigid bodies and soft bodies. It serves as a deterministic simulation framework, ensuring identical results across different platforms and architectures to support networked synchronization. The engine distinguishes itself through a focus on concurrent execution across multiple CPU cores to handle large numbers of active bodies. It provides specialized systems for vehicle physics, including wheeled and tracked models, as well as soft body physics for deformable objects and cloth. The simulation

Box2D is a 2D physics engine and rigid body simulator designed to compute collisions, forces, and joints in a two-dimensional plane. It functions as a collision detection library and a constraint-based physics solver that calculates the movement and interaction of solid objects using mass, friction, and restitution properties. The engine ensures consistency across different hardware architectures through a deterministic trigonometry implementation. It prevents high-speed objects from passing through boundaries using continuous collision detection and time-of-impact interpolation. The system

SciPy is a scientific computing library for Python that provides a comprehensive collection of mathematical algorithms and numerical tools for research and engineering. It functions as a high-performance numerical analysis framework, bridging high-level Python code with compiled C and Fortran routines to execute complex computations at hardware speeds. The library is built upon array-based data structures that utilize strided memory layouts to enable efficient data manipulation and slicing. By employing vectorized operation dispatch and linking to optimized hardware-specific linear algebra li

Rapier is a cross-platform physics engine and rigid body dynamics solver designed for 2D and 3D simulations. It functions as a collision detection system and a robotics simulation framework, providing a consistent API for calculating physical interactions across different environments. The engine distinguishes itself with specialized robotics capabilities, including a toolkit for importing URDF and STL models to control multibody chains. It supports precise mechanical movement through inverse kinematics calculations and the application of PID controllers for dynamic body control. The simulat

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

Riskfolio-Lib is a Python portfolio optimization library and convex risk management tool. It provides a framework for calculating optimal asset allocations using convex risk measures and mathematical programming solvers, supporting linear, quadratic, and semidefinite programming. The library features a hierarchical risk parity framework and financial asset clustering tools to group similar instruments and improve diversification. It includes a portfolio backtesting engine for simulating investment strategies using historical data and cross-validation. The system covers a broad range of quant

ManiSkill is a GPU-accelerated robot simulation framework designed for training robotic manipulation skills, benchmarking learning algorithms, and generating synthetic datasets. It serves as a reinforcement learning environment where robot control policies can be developed and evaluated using parallelized physics and rendering on the GPU. The platform is distinguished by its ability to perform sim-to-real transfer, allowing policies trained in virtual environments to be deployed onto physical robotic hardware. It features ray-traced parallel rendering for producing high-frame-rate RGBD and se

PhysicsJS is a JavaScript physics engine and 2D rigid body simulator designed to calculate the collisions, constraints, and dynamics of physical bodies. It functions as a modular physics library for simulating the movement and interaction of circular bodies and convex polygons. The engine implements constraint-based dynamics to enforce distance and angle constraints between objects, enabling the creation of articulated structures and linked physics. It utilizes impulse-based resolution to handle collisions and prevent objects from passing through one another. The library provides capabilitie

NumPy is a foundational library for scientific computing in Python, providing a comprehensive framework for managing and manipulating large-scale numerical information. It centers on high-performance multidimensional array objects that serve as the primary data structure for complex mathematical operations and data analysis workflows. The library distinguishes itself through specialized mechanisms for handling multidimensional data, including advanced indexing, slicing, and broadcasting techniques that allow for efficient operations across arrays of varying shapes. It utilizes strided metadat

scikit-opt is a Python optimization library and numerical framework designed to solve complex global optimization problems. It provides a suite of metaheuristic algorithms and tools for finding global minima or maxima of objective functions. The library implements a variety of nature-inspired and swarm intelligence algorithms, including Genetic Algorithms, Particle Swarm Optimization, Differential Evolution, Simulated Annealing, and Ant Colony Optimization. It includes specialized solvers for discrete combinatorial challenges, such as the Traveling Salesman Problem. The framework supports th

pyslam is a framework for Simultaneous Localization and Mapping that combines Python flexibility with C++ performance. It is a sparse SLAM implementation designed to map environment geometry and track device location by processing image frames into 3D points. The project features a bridge for exposing high-performance C++ classes to Python scripts using zero-copy memory sharing. This integration allows for switching between a scripting interface for rapid prototyping and a compiled core for execution speed. The system includes a spatial map optimizer to refine 3D point and camera pose estima

dm_control is a physics-based simulation framework and robot control simulation toolkit designed for creating and interacting with continuous control tasks. It serves as a suite of reinforcement learning environments and a benchmarking tool for evaluating autonomous agents within virtual physics spaces. The framework provides a collection of environments based on MuJoCo physics bindings to simulate rigid body dynamics and contact forces. It features hardware-accelerated rendering and interactive viewers for the visualization of physics environments and agent behavior. The system supports the

GnuCash is a double-entry accounting software designed for personal and small-business financial management. It tracks assets, liabilities, income, and expenses using a bookkeeping system that ensures financial accuracy. The platform functions as a multi-currency bookkeeping system and a SQL-based financial ledger, persisting accounting data in relational databases or XML files. The system is distinguished by its extensibility as a Python-scriptable accounting tool, providing Python bindings and a REPL for automating tasks and creating custom reports. It also serves as an investment portfolio