Justin Yim

EECS Department, University of California, Berkeley

Technical Report No. UCB/EECS-2020-108

May 29, 2020

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-108.pdf

Jumping is an exciting locomotion mode that can enable small ground-based robots to maneuver around large obstacles and gaps. A high-power jumping robot can rapidly traverse obstacles, but the resulting fast and forceful stance phases are challenging for control and estimation. This dissertation presents control and estimation for precise hopping, operation using only onboard sensors, and precise leaps and balanced landings. These algorithms place an emphasis on simple models of motion to gain insights about jumping dynamics and to derive simple programs that can run on a small robot's computationally-limited onboard processor.

Control and estimation algorithms are experimentally demonstrated with Salto-1P, a small 0.1 kg robot with a 0.15 m leg exhibiting a 1.83 m/s vertical jumping agility, the highest of any untethered electrically actuated robot when introduced. First, with precise foot placement, Salto-1P climbs and descends obstacles higher than its bodylength without missing a step or crashing. Second, onboard estimation of attitude and jumping velocity enable Salto-1P to operate without offboard sensing or processing and run fully autonomously or accept human guidance to hop outdoors. Finally, using high-performance balance control, Salto-1P demonstrates precisely targeted leaps and balanced landings to jump to and stand on narrow targets.

Advisors: Ronald S. Fearing

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BibTeX citation:

@phdthesis{Yim:EECS-2020-108,
    Author= {Yim, Justin},
    Title= {Hopping Control and Estimation for a High-performance Monopedal Robot, Salto-1P},
    School= {EECS Department, University of California, Berkeley},
    Year= {2020},
    Month= {May},
    Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-108.html},
    Number= {UCB/EECS-2020-108},
    Abstract= {Jumping is an exciting locomotion mode that can enable small ground-based robots to maneuver around large obstacles and gaps.  A high-power jumping robot can rapidly traverse obstacles, but the resulting fast and forceful stance phases are challenging for control and estimation.  This dissertation presents control and estimation for precise hopping, operation using only onboard sensors, and precise leaps and balanced landings.  These algorithms place an emphasis on simple models of motion to gain insights about jumping dynamics and to derive simple programs that can run on a small robot's computationally-limited onboard processor.

Control and estimation algorithms are experimentally demonstrated with Salto-1P, a small 0.1 kg robot with a 0.15 m leg exhibiting a 1.83 m/s vertical jumping agility, the highest of any untethered electrically actuated robot when introduced.  First, with precise foot placement, Salto-1P climbs and descends obstacles higher than its bodylength without missing a step or crashing.  Second, onboard estimation of attitude and jumping velocity enable Salto-1P to operate without offboard sensing or processing and run fully autonomously or accept human guidance to hop outdoors. 
 Finally, using high-performance balance control, Salto-1P demonstrates precisely targeted leaps and balanced landings to jump to and stand on narrow targets.},
}

EndNote citation:

%0 Thesis
%A Yim, Justin 
%T Hopping Control and Estimation for a High-performance Monopedal Robot, Salto-1P
%I EECS Department, University of California, Berkeley
%D 2020
%8 May 29
%@ UCB/EECS-2020-108
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2020/EECS-2020-108.html
%F Yim:EECS-2020-108