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Eric Li 0001

dblp:82/3391-1 · also Quan Bing Eric Li · DBLP profile ↗
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10ranked-venue papers
0as first author
7since 2021 · last 2026
0000-0001-9656-9258ORCID · verified

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

Artificial intelligence and machine learning · 7 · 4 since 2021Systems, architecture and hardware · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 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.

Computer graphics and multimedia
1 paper
Computational fabrication · 100%
Human-computer interaction and pervasive computing
1 paper
Human-robot interaction · 100%
Artificial intelligence
1 paper
Motion planning and robot control · 100%

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

TopicWeightPapersLastEvidence papers
Computational fabrication › origami design
origami mechanism
0.912025
Development of Bioinspired Five-DOF Origami for Robotic Spine Assistive Exoskeleton · IEEE Trans. Robotics 2025
Computational fabrication › soft robotics
soft robot design
0.912025
Development of Bioinspired Five-DOF Origami for Robotic Spine Assistive Exoskeleton · IEEE Trans. Robotics 2025
Human-robot interaction › assistive robotics
exoskeleton design
0.912025
Development of Bioinspired Five-DOF Origami for Robotic Spine Assistive Exoskeleton · IEEE Trans. Robotics 2025
Robotics › Motion planning and robot control › robot control
adaptive control
0.312025
Development of Bioinspired Five-DOF Origami for Robotic Spine Assistive Exoskeleton · IEEE Trans. Robotics 2025
Robotics › Motion planning and robot control
robot control
0.312025
Development of Bioinspired Five-DOF Origami for Robotic Spine Assistive Exoskeleton · IEEE Trans. Robotics 2025

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

cable-driven actuation · 2.6under-actuated mechanism · 1.7underactuated mechanism · 0.9
YearPublicationVenuePosition
2026 EDGAN: a novel GAN framework incorporating a diversity discriminator for robust data generation
Aiguo Cheng, Caiyu Ma, Zhicheng He 0004, Hexin Jiang, Eric Li 0001
Appl. Intell.5
2025 Investigating 3D object detection using stereo camera and LiDAR fusion with bird's-eye view representation
Zhicheng He 0004, Aiguo Cheng, Shengshi Zhong, Eric Li 0001
Neurocomputing6
2025 Development of Bioinspired Five-DOF Origami for Robotic Spine Assistive Exoskeleton
abstract
Frequent and high-load manual material handling (MMH) tasks often cause back injuries to the workers, and backsupport exoskeletons are developed for individuals with MMH tasks. However, these exoskeletons usually cannot adapt well to the movements of the wearer's spine. This paper introduces a new bio-inspired 5-DOF origami, and via mechanical design, a unique rigid-flexible coupled bio-inspired origami mechanism is proposed. This origami mechanism is compact and lightweight, and it has stable kinematic behaviors. With the designed origami mechanisms, a novel active origami-based robotic spine assistive exoskeleton (OSAE) is developed to assist individuals with MMH tasks during the symmetric and asymmetric lifting. The OSAE is actuated by a cable-driven module through an under-actuated spine module that consists of seven origami mechanisms. With the designed spine module, the OSAE can adapt well to the wearer's spine motions during MMH tasks. Modeling of the 5- DOF origami is described, and an adaptive control strategy is proposed for the exoskeleton to adapt to different lifting methods and objects with different weights. The experimental results demonstrate the effectiveness of the proposed OSAE. During the symmetric lifting of a 10-kg object, a reduction of 41.28% of the average muscle activity of the wearer's lumbar erector spinae muscle (LES) is observed, and reductions of 30.15% and 39.54% of the average muscle activities of the wearer's left and right LES are observed, respectively, during the asymmetric lifting of a 10- kg object.
Bing Chen 0005, Xiang Ni, Lei Zhou 0029, Bin Zi, Eric Li 0001, Dan Zhang 0006
IEEE Trans. Robotics5
2024 Robust locally nonlinear embedding (RLNE) for dimensionality reduction of high-dimensional data with noise
Eric Li 0001
Neurocomputing2
2024 A minimum complexity interaction echo state network
Xu Xu 0004, Eric Li 0001
Neural Comput. Appl.3
2023 A novel marine predators algorithm with adaptive update strategy
Zhicheng He 0004, Eric Li 0001, Yuanyi Huang
J. Supercomput.4
2022 A novel efficient method for welding spots detection
Zhicheng He 0004, Yadong Ma, Eric Li 0001
Multim. Tools Appl.4
2020 The feedback artificial tree (FAT) algorithm
Zhicheng He 0004, Eric Li 0001
Soft Comput.3
2017 The artificial tree (AT) algorithm
Zhicheng He 0004, Eric Li 0001, Aiguo Cheng
Eng. Appl. Artif. Intell.4
2017 Stability and instability of a neuron network with excitatory and inhibitory small-world connections
Dongyuan Yu, Xu Xu 0004, Eric Li 0001
Neural Networks4