Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data.

Nam Phuong Dam

dblp:373/6518 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0007-9612-230XORCID · 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 · 100%

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

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › robot sensing
proximity sensing
0.912025
Vision-Based Proximity and Tactile Sensing for Robot Arms: Design, Perception, and Control · IEEE Trans. Robotics 2025
Robotics › Robot manipulation
tactile sensing
0.912025
Vision-Based Proximity and Tactile Sensing for Robot Arms: Design, Perception, and Control · IEEE Trans. Robotics 2025
Robotics › Robot manipulation › soft robotics
soft robot control
0.312025
Vision-Based Proximity and Tactile Sensing for Robot Arms: Design, Perception, and Control · IEEE Trans. Robotics 2025

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

vision-based sensing · 0.9learning pipeline · 0.9
YearPublicationVenuePosition
2025 Vision-Based Proximity and Tactile Sensing for Robot Arms: Design, Perception, and Control
abstract
Soft-bodied robots with multimodal sensing capabilities hold promise for versatile and user-friendly robotics. However, seamlessly integrating multiple sensing functionalities into soft artificial skins remains a challenge due to compatibility issues between soft materials and conventional electronics. While vision-based tactile sensing has enabled simple and effective sensor designs for robotic touch, there has been limited exploration of this technique for intrinsic multimodal sensing in large-sized soft robot bodies. To address this gap, this paper introduces a novel vision-based soft sensing technique, named ProTac, capable of operating either in tactile or proximity sensing modes. This vision-based sensing technology relies on a soft functional skin that can actively switch its optical properties between opaque and transparent states. Furthermore, the paper develops efficient learning pipelines for proximity and tactile perceptions, as well as sensing strategies enabled through the timing activation of the two sensing modes. The effectiveness of the soft sensing technology is demonstrated through a soft ProTac link, which can be integrated into newly constructed or existing commercial robot arms. Results suggest that robots integrated with the ProTac link, along with rigorous control formulation can perform safe and purposeful control actions, which enhances human-robot interaction scenarios and facilitates motion control tasks that are challenging to achieve with conventional rigid links. Supplementary video:https://youtu.be/dFgZLUpeWw4Project website:https://quan-luu.github.io/protac-website/
Quan Khanh Luu, Dinh Quang Nguyen, Nhan Huu Nguyen, Nam Phuong Dam, Van Anh Ho
IEEE Trans. Robotics4