In recent years, a large number of manipulator robots have been deployed to replace or
assist humans in many repetitive and dangerous tasks. Yet, these robots have complex …

The exponential advancement in artificial intelligence (AI), machine learning, robotics, and
automation are rapidly transforming industries and societies across the world. The way we …

The dm_control software package is a collection of Python libraries and task suites for
reinforcement learning agents in an articulated-body simulation. Infrastructure includes a …

The DeepMind Control Suite is a set of continuous control tasks with a standardised
structure and interpretable rewards, intended to serve as performance benchmarks for …

Reinforcement learning (RL) techniques optimize the accumulated long-term reward of a
suitably chosen reward function. However, designing such a reward function often requires …

We consider the problem of generating motion plans for a robot that are guaranteed to
succeed despite uncertainty in the environment, parametric model uncertainty, and …

Underactuated robotics is an emerging research direction in the field of robotics. The control
input of the underactuated robot is less than the degree of freedom of the system. It has the …

Изучается проблема управления системами, содержащими неустойчивый объект.
Развиты методы синтеза управления системами со степенью неустойчивости не …

This book introduces a new approach to the study of systems, living or artificial, that can
learn from experience, and in so doing it indicates a new focus of activity within Artificial …

In this note, a high-order disturbance observer for a class of underactuated robotic systems
with mismatched uncertainties is proposed. To improve its estimation performance, a choice …