Dual Agent Learning Based Aerial Trajectory Tracking

Autor: Garg, Shaswat, Masnavi, Houman, Fidan, Baris, Janabi-Sharifi, Farrokh

This paper presents a novel reinforcement learning framework for trajectory tracking of unmanned aerial vehicles in cluttered environments using a dual-agent architecture. Traditional optimization methods for trajectory tracking face significant comp

Externí odkaz: http://arxiv.org/abs/2410.23571

Differential parametrization of rail vehicle properties and its impact on hunting.

Autor: Vishnu, S, Garg, Shaswat, Singh, SP, Saha, SK

Publikováno v: Proceedings of the Institution of Mechanical Engineers -- Part F -- Journal of Rail & Rapid Transit (Sage Publications, Ltd.); Jan2024, Vol. 238 Issue 1, p48-58, 11p