Emerging trends in realistic robotic simulations: A comprehensive systematic literature review
Simulation plays a pivotal role in providing safely reproducible scenarios to evaluate the
ever-advancing domain of computer science and robotics. It was an essential part of the …
ever-advancing domain of computer science and robotics. It was an essential part of the …
Learning local urban wind flow fields from range sensing
Obtaining accurate and timely predictions of the wind through an urban environment is a
challenging task, but has wide-ranging implications for the safety and efficiency of …
challenging task, but has wide-ranging implications for the safety and efficiency of …
Non-Prehensile Aerial Manipulation using Model-Based Deep Reinforcement Learning
CA Dimmig, M Kobilarov - 2024 IEEE 20th International …, 2024 - ieeexplore.ieee.org
With the continual adoption of Uncrewed Aerial Vehicles (UAVs) across a wide-variety of
application spaces, robust aerial manipulation remains a key research challenge. Aerial …
application spaces, robust aerial manipulation remains a key research challenge. Aerial …
URoBench: Comparative Analyses of Underwater Robotics Simulators from Reinforcement Learning Perspective
In an effort to standardise the evaluation of Reinforcement Learning (RL) algorithms across
different simulators of underwater robots, this paper introduces a benchmark framework …
different simulators of underwater robots, this paper introduces a benchmark framework …