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A software toolkit and hardware platform for investigating and comparing robot autonomy algorithms in simulation and reality

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arxiv 2206.06537 v1 pith:NXMHEVDE submitted 2022-06-14 cs.RO

Asher Elmquist , Aaron Young , Ishaan Mahajan , Kyle Fahey , Abhiraj Dashora , Sriram Ashokkumar , Stefan Caldararu , Victor Freire
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Xiangru Xu Radu Serban Dan Negrut
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classification cs.RO
keywords platformsimulationautonomyalgorithmsvehiclehardwarerealitysoftware
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We describe a software framework and a hardware platform used in tandem for the design and analysis of robot autonomy algorithms in simulation and reality. The software, which is open source, containerized, and operating system (OS) independent, has three main components: a ROS 2 interface to a C++ vehicle simulation framework (Chrono), which provides high-fidelity wheeled/tracked vehicle and sensor simulation; a basic ROS 2-based autonomy stack for algorithm design and testing; and, a development ecosystem which enables visualization, and hardware-in-the-loop experimentation in perception, state estimation, path planning, and controls. The accompanying hardware platform is a 1/6th scale vehicle augmented with reconfigurable mountings for computing, sensing, and tracking. Its purpose is to allow algorithms and sensor configurations to be physically tested and improved. Since this vehicle platform has a digital twin within the simulation environment, one can test and compare the same algorithms and autonomy stack in simulation and reality. This platform has been built with an eye towards characterizing and managing the simulation-to-reality gap. Herein, we describe how this platform is set up, deployed, and used to improve autonomy for mobility applications.

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    On a visually complex simulated track, a slim 3D CNN beat LSTM and GRU recurrent models on average lap time, but the model choice was made on the same test track.

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