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Navid Esfandiari

dblp:37/9969 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2012
0000-0003-0979-5236ORCID · corroborated

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
2 papers
Robot manipulation · 53% Motion planning and robot control · 42% Video understanding and tracking · 5%

Topics — the 7 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › micromanipulation
cell manipulation
0.112012
Controlled positioning of biological cells inside a micropipette · ICRA 2012
Robotics › Motion planning and robot control › robot control › feedback control
closed-loop positioning
0.112012
Controlled positioning of biological cells inside a micropipette · ICRA 2012
Robotics › Robot manipulation
micro/nano manipulation
0.112012
Controlled positioning of biological cells inside a micropipette · ICRA 2012
Robotics › Motion planning and robot control
robot control
0.112012
Controlled positioning of biological cells inside a micropipette · ICRA 2012
Robotics › Robot manipulation › micromanipulation
robotic cell manipulation
0.112011
Automated cell manipulation: Robotic ICSI · ICRA 2011
Robotics › Motion planning and robot control › robot control
motion control
0.012011
Automated cell manipulation: Robotic ICSI · ICRA 2011
Computer vision › Video understanding and tracking
object tracking
0.012011
Automated cell manipulation: Robotic ICSI · ICRA 2011

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

computer vision · 0.3robust control · 0.1motion control · 0.1
YearPublicationVenuePosition
2012 Controlled positioning of biological cells inside a micropipette
abstract
Manipulating single cells with a micropipette is the oldest, yet still a widely used technique. This paper discusses the positioning of a single cell to a target position inside the micropipette after the cell is aspirated into the micropipette. Due to the small volume of a single cell (pico-liter) and nonlinear dynamics involved, this task has high skill requirements and is labor intensive in manual operation that is solely based on trial and error and has high failure rates. We present automated techniques in this paper for achieving this task. Computer vision algorithm was developed to track a single cell inside a micropipette for automated single-cell positioning. A closed-loop robust controller integrating the dynamics of cell motion was designed to accurately and efficiently position the cell to a target position inside the micropipette. The system achieved high success rates of 97% for cell tracking (n=100) and demonstrated its capability of accurately positioning a cell inside the micropipette within 8 seconds (vs. 25 seconds by highly skilled operators).
Xuping Zhang, Clement Leung, Zhe Lu, Navid Esfandiari, Robert F. Casper, Yu Sun 0001
ICRA4
2011 Automated cell manipulation: Robotic ICSI
abstract
This paper is the first report of robotic ICSI (intracytoplasmic sperm injection). ICSI is a clinical procedure performed worldwide in fertility clinics, requiring pick-up of a single sperm and insert it into oocyte (i.e., an egg cell). Since its invention 20 years ago, ICSI has been conducted manually by a handful of highly skilled embryologists; however, success rates vary significantly among clinics due to poor reproducibility and inconsistency across operators. We leverage our work in robotic cell injection to realize robotic ICSI and aim ultimately, to standardize how clinical ICSI is performed. This paper presents some of the technical aspects of our robotic ICSI system, including a cell holding device and motion control and computer vision algorithms. The system performs visual tracking of single sperm, robotic immobilization of sperm, aspiration of sperm with pico-liter volume, and insertion of sperm into an oocyte with a high degree of reproducibility. The system requires minimal human involvement (requiring only a few computer mouse clicking), and is human operator skill independent. Using the hamster oocyte-human sperm model in preliminary trials, the robotic system demonstrated a high success rate of 90.0% and survival rate of 90.7% (n=120).
Zhe Lu, Xuping Zhang, Clement Leung, Navid Esfandiari, Robert F. Casper, Yu Sun 0001
ICRA4