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Fanghao Zhou

dblp:369/6820 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0003-4458-8635ORCID · reported

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

Applied, 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.

Artificial intelligence
1 paper
Robot manipulation · 67% Motion planning and robot control · 33%
Human-computer interaction and pervasive computing
1 paper
Haptics and multimodal interaction · 100%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
grasping
0.912025
Precise Control for Intrinsically Sensing Soft Robotic Tentacle With Free-Stroke TCA · IEEE Trans. Robotics 2025
Robotics › Robot manipulation › soft robotics
soft robot control
0.912025
Precise Control for Intrinsically Sensing Soft Robotic Tentacle With Free-Stroke TCA · IEEE Trans. Robotics 2025
Robotics › Motion planning and robot control › robot control
trajectory tracking
0.912025
Precise Control for Intrinsically Sensing Soft Robotic Tentacle With Free-Stroke TCA · IEEE Trans. Robotics 2025
Haptics and multimodal interaction
tactile sensing
0.312025
Precise Control for Intrinsically Sensing Soft Robotic Tentacle With Free-Stroke TCA · IEEE Trans. Robotics 2025

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

optical fiber sensing · 1.7multi-loop feedback control · 1.7twisted-and-coiled actuator · 0.9twisted and coiled actuator · 0.9
YearPublicationVenuePosition
2025 Precise Control for Intrinsically Sensing Soft Robotic Tentacle With Free-Stroke TCA
abstract
Twisted and Coiled Actuators (TCAs) are promising in soft robotics for their high energy density, light weight, and low voltage. However, current TCA-based soft robots face challenges of limited deformation and control precision, mainly due to the preloading requirement of TCAs and the lack of suitable intrinsic sensing capabilities. To address these issues, we designed a TCA with high load capacity, free stroke, and self-sensing capabilities, proposed flexible optical fiber-based posture and tactile sensing methods, and developed a multi-loop feedback controller. Collectively, these enable millimeter-level tracking accuracy in a soft tentacle robot. The TCA, with an optimized manufacturing process, achieves a 30% free stroke without preloading, a 32% improvement in ultimate stress, and temperature self-sensing capabilities with a maximum error of less than 6%. Combining the TCAs with compliant macro-bend optical fibers and soft optical waveguides, we created a soft robotic tentacle with intrinsic posture and tactile sensing, and designed a multi-input multi-output closed-loop and feedforward controller. Experiments demonstrate that the model-based feedforward significantly improves the control performance, reducing the rise time by 15.3%. The trajectory tracking error remains within the millimeter range, and the repetitive positioning error for hexagonal trajectories reaches sub-millimeter precision. The tactile sensor of the robot enables real-time perception of the object's modulus and pressing states. These findings highlight the soft robotic tentacle's potential for various applications, including underwater exploration, detection, and sampling.
Hongxin Huang, Zhongtian Liu, Zhetian Ding, Fanghao Zhou, Zheng Chen 0004, Tiefeng Li
IEEE Trans. Robotics5