Скачать с ютуб RoboHive - A unified framework for robot learning в хорошем качестве

RoboHive - A unified framework for robot learning

https://sites.google.com/view/robohive RoboHive, is a modular framework for research in the field of Robot Learning and Embodied AI. RoboHive ecosystem encompasses a range of pre-existing and novel environments, including dexterous manipulation with the Shadow Hand, whole arm manipulation tasks with Franka and Fetch robots, and various quadruped loco-motion tasks. In comparison to previous works, RoboHive offers a streamlined and unified task interface, utilizes the latest simulation bindings, features tasks with rich visual diversity, and supports common hardware drivers for real-world developments. The unified interface of RoboHive offers researchers a convenient and accessible platform to study a multitude of learning paradigms such as imitation, reinforcement, multi-task, and hierarchical learning. Furthermore, RoboHive includes expert demonstrations and baseline results for most environments, providing a standard for benchmarking and comparisons. Features: - Most extensive and diverse task collection - Fully customizable visually rich task designed for behavior generalization. - Rewards agnostic task success metrics - Support for diverse algorithmic families + pre-trained baselines - Sim & hardware agnostic robot class for easy transition between the two - Teleoperation support. Human+Expert dataset