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Gengliang Chen

dblp:304/4124 · DBLP profile ↗
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3ranked-venue papers
0as first author
3since 2021 · last 2025
0000-0002-5728-103XORCID · corroborated

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

Artificial intelligence and machine learning · 3 · 3 since 2021Systems, architecture and hardware · 3 · 3 since 2021

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
2 papers
Motion planning and robot control · 51% Robot manipulation · 29% Video understanding and tracking · 20%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
robot control
0.722022
An Indeterministic Vision-Based State Observer for Growing Magnetic Microrobot Motion Status Estimation · ICRA 2022
3D Periodic Magnetic Servoing System for Microrobot Actuation Using Decoupled Asynchronous Repetitive Control Approach · ICRA 2021
Computer vision › Video understanding and tracking › object tracking › discriminative tracking
correlation filter tracking
0.212022
An Indeterministic Vision-Based State Observer for Growing Magnetic Microrobot Motion Status Estimation · ICRA 2022
Computer vision › Video understanding and tracking
object tracking
0.212022
An Indeterministic Vision-Based State Observer for Growing Magnetic Microrobot Motion Status Estimation · ICRA 2022
Robotics › Motion planning and robot control › robot control › learning control
repetitive control
0.112021
3D Periodic Magnetic Servoing System for Microrobot Actuation Using Decoupled Asynchronous Repetitive Control Approach · ICRA 2021

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

sliding mode state estimation · 0.6discriminative correlation filter · 0.6magnetic field control · 0.5decoupled asynchronous repetitive control · 0.5
YearPublicationVenuePosition
2025 Asynchronous Rectification-Based Fast Local Imaging and Estimation Scheme for High-Speed Rotating States Observation of MM
abstract
Magnetic microrobots (MMs) have emerged as promising tools for targeted therapies, including non-invasive in vivo treatments and precise drug delivery, owing to their untethered controllability and biocompatibility. Current actuation strategies for MMs primarily rely on two magnetic field (MF) generation approaches: gradient-based and rotational methods. Unlike the gradient method, rotational actuation enables efficient manipulation of MMs under significantly weaker magnetic fields. To fully leverage the potential of rotationally driven MMs, a comprehensive understanding of their fundamental spin motility is essential. Achieving accurate characterization of these MMs necessitates the development of an MF generation system equipped with rapid motion-tracking and broad-range measurement capabilities. This study proposes a high-speed rotating states observation scheme by developing a tracking-based optimal local imaging and estimation scheme, simultaneously meeting the broad-range observation capability and the high imaging speed requirement. Specifically, the CSR-DCF tracking method is adopted to detect the MM’s location, and based on this, the observation system adjusts the imaging region optimally. An estimation scheme based on the asynchronous rectification method is derived to measure the MM rotating states consistently using measured MF data and local optical images of the target. Experimental studies are carried out to validate the effectiveness of the proposed scheme.
Zhiyong Sun 0002, Yu Cheng 0006, Gengliang Chen, Erkang Cheng
IROS3
2022 An Indeterministic Vision-Based State Observer for Growing Magnetic Microrobot Motion Status Estimation
abstract
To date, untethered micro/nanorobots have attracted considerable attention in various aspects due to their unique potential for in-vivo applications such as the targeted therapy. One of the most promising types of micro/nanorobots is the class of ferromagnetic microrobots which can be efficiently actuated via gradient/rotational magnetic field generated by less costly electromagnetic coil systems. For performing successful operations, locomotion control of the magnetic microrobots is non-trivial. Modern controllers commonly require motion status-based feedback. To fully utilize those advanced approaches, motion state of one microrobot should be supplied, however it is still challenging in cases. It is noted that, during locomotion, one ferromagnetic microrobot can combine with others to form an unstructured larger one, namely growing magnetic microrobot (GMM), whose dynamic behavior keeps changing, and thus the model-based observers are never applicable. Besides, tracking and estimating states of those unstructured time-varying GMMs in complex surroundings are always challenging, especially for an uneven sampling scenario. In order to accurately estimate the GMM motion status in a complex environment via micro-vision, this study develops an indeterministic observer leveraging on the approach of discriminative correlation filter with channel/spatial reliability (CSR-DCF) and the variable-step finite-time sliding mode (FSM-V) state estimation theory. Experimental study verifies that the proposed observation scheme can effectively estimate motion states of one GMM moving in obstacle surroundings throughout.
Zhiyong Sun 0002, Yu Cheng 0006, Erkang Cheng, Gengliang Chen, Lixin Dong
ICRA5
2021 3D Periodic Magnetic Servoing System for Microrobot Actuation Using Decoupled Asynchronous Repetitive Control Approach
abstract
To date, untethered microrobots have been receiving tremendous attention for playing implacable roles of maneuverable tools in fields such as microfabrication and biomanipulation. Typical actuation of such untethered tiny robots is the magnetic field-based approaches, including gradient and rotational methods. Compared to the gradient type method, the rotational approach requires much less magnetic field strength to generate efficient actuation for magnetic microrobots. To actuate microrobots desirably, a precise periodic magnetic field should be provided. To generate precise periodic magnetic field with enhanced strength, this paper develops a prototype of 3D magnetic servoing system based on integrated solenoids, performance of which are enhanced by employing iron cores and extended number of coils. Each solenoid is equipped with a Hall sensor to provide real-time feedback signal for performing precise magnetic field control. To precisely regulate this setup, a decoupled asynchronous repetitive control (DARC) scheme is established to generate a desirable 3D periodic magnetic field with noise-level tracking error under the situation of missing execution opportunity randomly. Experimental results demonstrate the effectiveness of the proposed magnetic servoing system, which is promising for dynamic properties characterization of magnetic microrobots.
Zhiyong Sun 0002, Yu Cheng 0006, Erkang Cheng, Gengliang Chen, Lixin Dong
ICRA5