TY - JOUR
T1 - Micromanipulation Using Reconfigurable Self-Assembled Magnetic Droplets With Needle Guidance
AU - Wang, Qianqian
AU - Yang, Lidong
AU - Zhang, Li
N1 - Funding:
This work was supported in part by the Innovation and Technology Funds (ITF) projects funded by the HKSAR Innovation
and Technology Commission (ITC) under Project ITS/231/15 and Project MRP/036/18X and in part by the Multi-Scale Medical Robotics Center (MRC), InnoHK, at the Hong Kong Science Park.
Publisher Copyright:
© 2004-2012 IEEE.
PY - 2022/4
Y1 - 2022/4
N2 - A dynamic self-assembly is a promising approach for inducing the collective behavior of agents to perform coordinated tasks at small scales. However, efficient pattern formation and navigation in environments with complex conditions remain a challenge. In this article, we propose a strategy for micromanipulation using dynamically self-assembled magnetic droplets with needle guidance. An iron needle was controlled by a three-degree-of-freedom (3-DoF) manipulator and magnetized by precessing magnetic fields. The process of self-assembly was optimized based on real-time vision feedback and a genetic algorithm. Affected by the locally induced field gradient near the needle, reconfigurable assembled magnetic droplets were formed beneath the air-liquid interface with high time efficiency, and the geometric center of the pattern was determined. Following the magnetized needle, assembled patterns were navigated along preplanned paths and exhibited reversible pattern expansion and shrinkage. Moreover, cargo can be trapped and caged by exploiting the induced fluid flow around the assembled droplets. To perform cargo transportation tasks in a multiple-obstacle environment, an optimal path planner with obstacle-avoidance capability was designed based on the particle swarm optimization (PSO) algorithm. Experiments demonstrated effective pattern formation, navigation, cargo trapping, and obstacle-avoidance transportation. The proposed method opens new prospects of using a dynamically self-assembled pattern as an untethered end-effector for micromanipulation. Note to Practitioners - This article was motivated by the recent interest in utilizing the collective behavior of small-scale active agents to perform micromanipulation tasks. Driven by external magnetic fields, building blocks are gathered and assembled, yielding a dynamically stable pattern. To perform practical tasks, efficient pattern formation, control, and navigation are required. Besides, obstacles often exist in the working environment, challenging pattern navigation, and manipulation tasks. The strategy presented here is developed for micromanipulation using dynamically self-assembled magnetic droplets with needle guidance. The three-axis Helmholtz coil system is applied to rotate the droplets and magnetize the iron needle. Algorithms are designed to guide and optimize the pattern formation, navigation, and cargo trapping process. Magnetic droplets are real-time tracked, and ordered assembled patterns are formed in an optimized way. Following the needle, the pattern was navigated and performed cargo manipulation tasks with obstacle-avoidance capability. Experimental results have validated the proposed strategy in pattern formation, navigation, and cargo manipulation in a multiple-obstacle environment.
AB - A dynamic self-assembly is a promising approach for inducing the collective behavior of agents to perform coordinated tasks at small scales. However, efficient pattern formation and navigation in environments with complex conditions remain a challenge. In this article, we propose a strategy for micromanipulation using dynamically self-assembled magnetic droplets with needle guidance. An iron needle was controlled by a three-degree-of-freedom (3-DoF) manipulator and magnetized by precessing magnetic fields. The process of self-assembly was optimized based on real-time vision feedback and a genetic algorithm. Affected by the locally induced field gradient near the needle, reconfigurable assembled magnetic droplets were formed beneath the air-liquid interface with high time efficiency, and the geometric center of the pattern was determined. Following the magnetized needle, assembled patterns were navigated along preplanned paths and exhibited reversible pattern expansion and shrinkage. Moreover, cargo can be trapped and caged by exploiting the induced fluid flow around the assembled droplets. To perform cargo transportation tasks in a multiple-obstacle environment, an optimal path planner with obstacle-avoidance capability was designed based on the particle swarm optimization (PSO) algorithm. Experiments demonstrated effective pattern formation, navigation, cargo trapping, and obstacle-avoidance transportation. The proposed method opens new prospects of using a dynamically self-assembled pattern as an untethered end-effector for micromanipulation. Note to Practitioners - This article was motivated by the recent interest in utilizing the collective behavior of small-scale active agents to perform micromanipulation tasks. Driven by external magnetic fields, building blocks are gathered and assembled, yielding a dynamically stable pattern. To perform practical tasks, efficient pattern formation, control, and navigation are required. Besides, obstacles often exist in the working environment, challenging pattern navigation, and manipulation tasks. The strategy presented here is developed for micromanipulation using dynamically self-assembled magnetic droplets with needle guidance. The three-axis Helmholtz coil system is applied to rotate the droplets and magnetize the iron needle. Algorithms are designed to guide and optimize the pattern formation, navigation, and cargo trapping process. Magnetic droplets are real-time tracked, and ordered assembled patterns are formed in an optimized way. Following the needle, the pattern was navigated and performed cargo manipulation tasks with obstacle-avoidance capability. Experimental results have validated the proposed strategy in pattern formation, navigation, and cargo manipulation in a multiple-obstacle environment.
KW - Collective behavior
KW - dynamic self-assembly
KW - micromanipulation
KW - small-scale robot
KW - swarm control
UR - http://www.scopus.com/inward/record.url?scp=85103196755&partnerID=8YFLogxK
U2 - 10.1109/TASE.2021.3062779
DO - 10.1109/TASE.2021.3062779
M3 - Journal article
AN - SCOPUS:85103196755
SN - 1545-5955
VL - 19
SP - 759
EP - 771
JO - IEEE Transactions on Automation Science and Engineering
JF - IEEE Transactions on Automation Science and Engineering
IS - 2
ER -