A Framework for Visually Realistic Multi-robot Simulation in Natural Environment

TL;DR

This paper introduces a versatile framework using Unreal Engine4 for realistic multi-robot and drone simulation in natural environments, enabling testing of vision algorithms under diverse conditions.

Contribution

The paper presents a novel simulation architecture that generates realistic sensor data and environmental effects for multiple robots and drones in complex natural settings.

Findings

Effective simulation of sensor outputs in natural environments

Validation of drone tracking in complex scenarios

Support for testing vision algorithms under environmental effects

Abstract

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.