FastSim: A Modular and Plug-and-Play Simulator for Aerial Robots

State-of-the-art robotics simulators are equipped with well-established mapping, planning, and control systems. However, they lack modularity and the convenience of plug-and-play functionality. In this work, we present FastSim, a high-fidelity and user-friendly simulation framework based on the Unit...

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Vydáno v:IEEE robotics and automation letters Ročník 9; číslo 6; s. 5823 - 5830
Hlavní autoři: Cui, Can, Zhou, Xiaobin, Wang, Miao, Gao, Fei, Xu, Chao
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 01.06.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Aerial systems: applications
Algorithms
Animation
Autonomous aerial vehicles
Decoupling
Design methodology
Drones
Engines
Hardware-in-the-loop simulation
Image quality
Image sensors
methods and tools for robot system design
Mixed reality
Modularity
Performance evaluation
Plug & play
Robot dynamics
Robot sensing systems
Robotics
Robots
Rotors
Sensors
Simulation
simulation and animation
Simulator fidelity
Simulators
Visualization
ISSN:2377-3766, 2377-3766
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Popis
Shrnutí:State-of-the-art robotics simulators are equipped with well-established mapping, planning, and control systems. However, they lack modularity and the convenience of plug-and-play functionality. In this work, we present FastSim, a high-fidelity and user-friendly simulation framework based on the Unity engine. FastSim enables users to build robot simulation scenarios efficiently, by decoupling various simulation tasks with customizable modules, which contains simulated sensors, integrated utilities, visualization tools, and template robots. Besides high-performance robot dynamics simulation and high-quality image rendering, hardware-in-the-loop and mixed-reality applications are also available in this framework. The distinguished merits of FastSim include: (1) Robot Operating System (ROS) compatible control interfaces and abundant visualization tools for researchers who prefer ROS-based toolchains and (2) its integration of state-of-the-art planning algorithms, which enables users, even beginners, to quickly master the deployment of highly autonomous robots in simulations. Finally, we demonstrate the flexibility of FastSim by several experiments and performance evaluations with open source examples in repository: https://github.com/ZJU-FAST-Lab/FastSim .
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ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2024.3391059