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Ellande Tang

dblp:205/3169 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · unresolved

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

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 2

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
Legged, aerial and field robots · 50% Motion planning and robot control · 50%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot control › adaptive control
adaptive nonlinear control
0.412020
Adaptive Nonlinear Control of Fixed-Wing VTOL with Airflow Vector Sensing · ICRA 2020
Robotics › Legged, aerial and field robots
aerial robot control
0.412020
Adaptive Nonlinear Control of Fixed-Wing VTOL with Airflow Vector Sensing · ICRA 2020
Robotics › Motion planning and robot control
robot control
0.412020
Adaptive Nonlinear Control of Fixed-Wing VTOL with Airflow Vector Sensing · ICRA 2020
Robotics › Legged, aerial and field robots › aerial robot control
VTOL UAV control
0.412020
Adaptive Nonlinear Control of Fixed-Wing VTOL with Airflow Vector Sensing · ICRA 2020

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

composite adaptation · 0.4airflow vector sensing · 0.4
YearPublicationVenuePosition
2020 Adaptive Nonlinear Control of Fixed-Wing VTOL with Airflow Vector Sensing
abstract
Fixed-wing vertical take-off and landing (VTOL) aircraft pose a unique control challenge that stems from complex aerodynamic interactions between wings and rotors. Thus, accurate estimation of external forces is indispensable for achieving high performance flight. In this paper, we present a composite adaptive nonlinear tracking controller for a fixed- wing VTOL. The method employs online adaptation of linear force models, and generates accurate estimation for wing and rotor forces in real-time based on information from a three-dimensional airflow sensor. The controller is implemented on a custom-built fixed-wing VTOL, which shows improved velocity tracking and force prediction during the transition stage from hover to forward flight, compared to baseline flight controllers.
Xichen Shi, Patrick Spieler, Ellande Tang, Elena-Sorina Lupu, Phillip Tokumaru, Soon-Jo Chung
ICRA3
2017 Inclined surface locomotion strategies for spherical tensegrity robots
abstract
This paper presents a new teleoperated spherical tensegrity robot capable of performing locomotion on steep inclined surfaces. With a novel control scheme centered around the simultaneous actuation of multiple cables, the robot demonstrates robust climbing on inclined surfaces in hardware experiments and speeds significantly faster than previous spherical tensegrity models. This robot is an improvement over other iterations in the TT-series and the first tensegrity to achieve reliable locomotion on inclined surfaces of up to 24°. We analyze locomotion in simulation and hardware under single and multi-cable actuation, and introduce two novel multi-cable actuation policies, suited for steep incline climbing and speed, respectively. We propose compelling justifications for the increased dynamic ability of the robot and motivate development of optimization algorithms able to take advantage of the robot's increased control authority.
Lee-Huang Chen, Brian Cera, Edward Zhu, Riley Edmunds, Franklin Rice, Antonia Bronars, Ellande Tang, Saunon R. Malekshahi, Osvaldo Romero, Adrian K. Agogino, Alice M. Agogino
IROS7