Robotic simulators are crucial for academic research and education as well as the
development of safety-critical applications. Reinforcement learning environments—simple …

Multi-rotor Unmanned Aerial Vehicles (UAVs), although originally designed and developed
for defence and military purposes, in the last ten years have gained momentum, especially …

In this letter, we introduce OmniDrones, an efficient and flexible platform tailored for
reinforcement learning in drone control, built on Nvidia's Omniverse Isaac Sim. It employs a …

Unmanned aerial vehicles offer a safe and fast approach to the production of three-
dimensional spatial data on the surrounding space. In this article, we present a low-cost …

Solar energy is one of the most strategic energy sources for the world's economic
development. This has caused the number of solar photovoltaic plants to increase around …

The use of drones to explore indoor spaces has gained attention and popularity for disaster
management and indoor navigation applications. In this paper we present the operations …

Drone simulations offer a safe environment for collecting data and testing algorithms.
However, the depth camera sensor in the simulation provides exact depth values without …

The embedded system developers often need to perform software testing even when the
target hardware is inaccessible. Due to the inaccessibility of the hardware, the hardware …

We investigate the sequential manipulation planning problem for unmanned aerial
manipulators (UAMs). Unlike prior UAM work that primarily focuses on one-step …

The design of racing drones brings quite a thrilling challenge from a flight dynamics point of
view. This work aims to offer a single-based simulation platform combining its geometric …