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Daniel J. Yang

dblp:249/3107 · DBLP profile ↗
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3ranked-venue papers
2as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3 · 2 first-authorSystems, architecture and hardware · 3 · 2 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Robot navigation and mapping · 44% Probabilistic and Bayesian machine learning · 44% Motion planning and robot control · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Probabilistic and Bayesian machine learning › statistical inference › bayesian inference › bayesian filtering › kalman filtering
extended kalman filter
0.412019
Modeling and state estimation of a Micro Ball-balancing Robot using a high yaw-rate dynamic model and an Extended Kalman Filter · ICRA 2019
Robotics › Robot navigation and mapping
state estimation
0.412019
Modeling and state estimation of a Micro Ball-balancing Robot using a high yaw-rate dynamic model and an Extended Kalman Filter · ICRA 2019
Robotics › Motion planning and robot control › robot control › stabilization control
balancing robot control
0.112019
Modeling and state estimation of a Micro Ball-balancing Robot using a high yaw-rate dynamic model and an Extended Kalman Filter · ICRA 2019

Methods — techniques the papers use, named apart from their topics

extended kalman filter · 0.4dynamic modeling · 0.4
YearPublicationVenuePosition
2019 Modeling and state estimation of a Micro Ball-balancing Robot using a high yaw-rate dynamic model and an Extended Kalman Filter
Eric Sihite, Daniel J. Yang, Thomas R. Bewley
ICRA2
2018 A minimalist Stair Climbing Robot (SCR) formed as a leg balancing & climbing Mobile Inverted Pendulum (MIP)
abstract
This paper presents a (patent-pending) small, quasi-static, minimal-complexity Stair Climbing Robot (SCR). The vehicle design is given simply by adding a third motor to a (Segway-like) Mobile Inverted Pendulum (MIP), enabling it to maneuver up stairs, leveraging feedback control, by planting it's “foot” onto the ground in front of the next step, lifting the chassis/wheel assembly up it's own “leg”, leaning over onto the top of the next step, self uprighting, and repeating for the following step(s). Fore/aft stabilization during leg balancing is given by using the MIP drive wheels as reaction wheels, while left/right stability is given by the width of the foot itself. The design is small and simple enough to potentially be ruggedized as a stair-climbing throwbot, akin to the Recon Scout (but able to climb up stairs) for reconnaissance in military and homeland security applications.
Daniel J. Yang, Thomas R. Bewley
IROS1
2015 Design and control of a micro ball-balancing robot (MBBR) with orthogonal midlatitude omniwheel placement
abstract
Ball-balancing robots (BBRs) are endowed with rich dynamics. When properly designed and stabilized via feedback to eliminate jitter, and intuitively coordinated with a well-designed smartphone interface, BBRs exhibit a uniquely fluid and organic motion. Unlike mobile inverted pendulums (MIPs, akin to unmanned Segways), BBRs stabilize both fore/aft and left/right motions with feedback, and bank when turning. Previous research on BBRs focused on vehicles from 50cm to 2m in height; the present work is the first to build significantly smaller BBRs, with heights under 25cm. We consider the unique issues arising when miniaturizing a BBR to such a scale, which are characterized by faster time scales and reduced weight (and, thus, reduced normal force and stiction between the omniwheels and the ball). Two key patent-pending aspects of our design are (a) moving the omniwheels to contact the ball down to around 20 to 30 deg N latitude, which increases the normal force between the omniwheels and the ball, and (b) orienting the omniwheels into mutually-orthogonal planes, which improves efficiency. Design iterations were facilitated by rapid prototyping and leveraged low-cost manufacturing principles and inexpensive components. Classical successive loop closure control strategies are implemented, which prove to be remarkably effective when the BBR isn't spinning quickly, and thus the left/right and fore/aft stabilization problems decompose into two decoupled MIP problems.
Daniel J. Yang, Eric Sihite, Jeffrey M. Friesen, Thomas R. Bewley
IROS1