A Framework for Visually Realistic Multi-robot Simulation in Natural Environment
This provides a tool for researchers and developers to test and validate computer vision algorithms for drones in realistic conditions, though it is incremental as it builds on existing simulation methods.
The paper presents a framework for simulating multiple robots and drones in realistic natural environments using Unreal Engine4 to generate optical and depth sensor data, and demonstrates its effectiveness with a test scenario where one drone tracks another in a complex environment.
This paper presents a generalized framework for the simulation of multiple robots and drones in highly realistic models of natural environments. The proposed simulation architecture uses the Unreal Engine4 for generating both optical and depth sensor outputs from any position and orientation within the environment and provides several key domain specific simulation capabilities. Various components and functionalities of the system have been discussed in detail. The simulation engine also allows users to test and validate a wide range of computer vision algorithms involving different drone configurations under many types of environmental effects such as wind gusts. The paper demonstrates the effectiveness of the system by giving experimental results for a test scenario where one drone tracks the simulated motion of another in a complex natural environment.