Modern parallel computers could power the perception and compression algorithms small planetary rovers require to navigate long distances, construct detailed terrain maps, and communicate discoveries to Earth. This work identifies and comprehensively characterizes four algorithms important to planetary roving that are well-suited for parallel computing. Multiple implementations of dense stereo matching, multi-view stereo, image compression, and triangle mesh compression are evaluated using the NVIDIA Jetson family of high-performance embedded computers. Image and mesh inputs are derived from simulation and used to evaluate the performance, power consumption, and hardware utilization of each device as a function of time. Our results demonstrate the promising capacity for modern embedded computers to expand the range and pace of planetary rover exploration.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    High Performance Computing for Autonomous Planetary Exploration


    Contributors:


    Publication date :

    2021-07-01


    Size :

    7635723 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Planetary Surface Exploration Mesur/Autonomous Lunar Rover

    L. Stauffer / M. Dilorenzo / D. Austin et al. | NTIS | 1992


    Planetary surface exploration: MESUR/autonomous lunar rover

    Stauffer, Larry / Dilorenzo, Matt / Austin, Dave et al. | NTRS | 1992


    Autonomous Navigation of Rovers for Planetary Exploration

    Schilling, K. / International Federation of Automatic Control | British Library Conference Proceedings | 1999


    Planetary surface exploration MESUR/autonomous lunar rover

    Stauffer, Larry / Dilorenzo, Matt / Austin, Dave et al. | NTRS | 1992


    Planetary Surface Exploration: MESUR/Autonomous Lunar Rover

    L. Stauffer / M. Dilorenzo / D. Austin et al. | NTIS | 1992