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Robot Grasping Dataset
The dataset used in this paper is a robot grasping dataset, where the robot learns to grasp objects in a simulated environment. -
Simulation Parameters and Results for mmWave and LTE Connections
Simulation parameters and results for mmWave and LTE connections -
Simulated Non-Gaussian Data
The dataset used in this paper is a simulated non-Gaussian data. -
Simulation results
The dataset used in this paper is a set of simulation results for distinguishing between physical faults and cyberattacks. -
SoMoSiMu-Bench: A Benchmark for Social Movement Simulation
A Twitter-like environment and a benchmark SoMoSiMu-Bench for simulation and evaluation of social media user simulation. -
AADS: Augmented autonomous driving simulation using data-driven algorithms
AADS: Augmented autonomous driving simulation using data-driven algorithms. -
Simulated Environments and Networks
A dataset for simulating linear and nonlinear dynamic systems, with measurements received over a network. -
Simulations
The dataset used in this paper is a sample of 1,000, 3,000, 5,000, and 10,000 observations. -
Design and use paradigms for gazebo, an open-source multi-robot simulator
Design and use paradigms for gazebo, an open-source multi-robot simulator. -
Augmented LiDAR Simulator for Autonomous Driving
A LiDAR simulator for autonomous driving that generates annotated point cloud data. -
Electric Vehicle Charging Dataset
The dataset used in this paper is a simulation case study on cyberattack scenarios on a plug-in electric-vehicle (PEV) through the electric vehicle supply equipment (EVSE) at... -
Forced Homogeneous Isotropic Turbulence
The dataset used in this paper for training a reinforcement learning model for turbulence modeling in large eddy simulations. -
LES Environment
The dataset used in this paper for testing the trained reinforcement learning model for turbulence modeling in large eddy simulations. -
DSSE: a Drone Swarm Search Environment
A Drone Swarm Search environment, based on PETTINGZOO, that is to be used in conjunction with multi-agent (or single-agent) reinforcement learning algorithms. -
Autonomous Braking System via Deep Reinforcement Learning
The proposed autonomous braking system learns an intelligent way of brake control from the experiences obtained under the simulated environment. -
Ray-Tracing Simulation
A ray-tracing simulation was conducted to predict pseudorange biases caused by reflections due to buildings in an urban environment. -
3D Terrain and Building Map
A 3D terrain and building map of the simulation area and 3D terrain and building map from 3dbuildings. -
Simulated Case Study
A simulated case study is designed to evaluate the performances of the proposed approaches under known and controlled conditions. -
Simulated scenarios
Simulated scenarios for testing the proposed methodology.