Projects sharing features with Crocoddyl

UniAD is a unified deep learning framework for autonomous driving that integrates perception, prediction, and planning into a single end-to-end model. It functions as a neural network architecture that maps raw sensor data directly to driving trajectories and motion plans. This project serves as a research implementation of a planning-oriented approach that jointly trains occupancy, mapping, and object tracking modules. It employs a multi-task perception framework to optimize overall driving performance. The system covers a broad capability surface including end-to-end driving pipelines, veh

Simplifying optimal control with metaprogramming

Gaussian Process Motion Planner 2

This project is a comprehensive research platform designed for the end-to-end lifecycle of robotic learning. It provides a modular framework for training neural network policies—specifically through imitation and reinforcement learning—and deploying them onto physical robotic hardware. By offering a unified interface for hardware abstraction, the platform decouples high-level control logic from the specific sensors and actuators of diverse robotic systems. The framework distinguishes itself through a standardized approach to data and policy management. It utilizes a consistent schema for reco

robotic motion planning library

The Kautham project

Extensible Optimization Framework

Open3D is a software toolkit designed for the processing, alignment, and reconstruction of three-dimensional data. It functions as a computer vision geometry engine that enables the manipulation of point clouds, meshes, and volumetric grids derived from sensor inputs. The library distinguishes itself through a high-performance computational core that executes geometric processing tasks in native code, paired with a binding layer that exposes these capabilities to high-level languages for rapid prototyping. It provides specialized algorithms for spatial registration, allowing users to merge mu

Trajectory Optimization

Optimal Control for Switched Systems

Behavior Trees Library for ROS (Robot Operating System). In C++ and python

:robot: The MoveIt motion planning framework

Motion Generation for Robots and Machines. Real-time. Jerk-constrained. Time-optimal.

Artificial Intelligence for Kinematics, Dynamics, and Optimization

A Python implementation of the Robotics Toolbox for MATLAB ® GitHub repository Documentation ICRA Paper Wiki (examples and details)

An optimization framework that links CasADi, Ipopt, ACADOS and biorbd for Optimal Control Problem

Rerun is a multimodal data visualizer and robotics data logger designed for rendering synchronized streams of 3D spatial data, images, and time-series metrics. It functions as a tool for capturing high-frequency sensor data and AI outputs into a queryable columnar format, providing a dedicated interface for viewing MCAP recording files and analyzing physical environments. The project distinguishes itself as a machine learning dataset streamer, capable of feeding logged recordings directly into GPU buffers and PyTorch training pipelines without intermediate exports. It supports a high-performa

A fast trajectory optimization library written in Julia

The Robotics Library (RL) is a self-contained C++ library for rigid body kinematics and dynamics, motion planning, and control.

Pinocchio is a multi-body dynamics engine and rigid body physics library designed for computing forward and inverse kinematics and dynamics for articulated rigid-body systems. It functions as a robot kinematics solver and model parser, enabling the analysis of complex robotic systems through kinematic and dynamic computations. The project distinguishes itself with specialized capabilities for constrained dynamics, including the calculation of contact impulses and centroidal momentum. It provides a parallel processing collision detection system for computing minimal distances between rigid bod

Time-optimal Trajectory Generation and Control

Humanoid robotics prototyping environment based on OpenRAVE

GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.

Ceres Solver is a C++ library for numerical optimization, specializing in non-linear least squares and unconstrained optimization problems. It serves as a framework for automatic differentiation and robust curve fitting, providing tools to solve large-scale mathematical models. The library is distinguished by its bundle adjustment capabilities, which exploit sparse matrix structures to refine 3D scene points and camera parameters. It utilizes dual-number automatic differentiation to compute derivatives of cost functions, removing the need for manual Jacobian derivation. The project covers a

The Control Toolbox - An Open-Source C++ Library for Robotics, Optimal and Model Predictive Control