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IROS 2021

Autonomous object harvesting using synchronized optoelectronic microrobots

Conference Paper Accepted Paper Artificial Intelligence ยท Robotics

Abstract

Optoelectronic tweezer-driven microrobots (OETdMs) are a versatile micromanipulation technology based on the application of light induced dielectrophoresis to move small dielectric structures (microrobots) across a photoconductive substrate. The microrobots in turn can be used to exert forces on secondary objects and carry out a wide range of micromanipulation operations, including collecting, transporting and depositing microscopic cargos. In contrast to alternative (direct) micromanipulation techniques, OETdMs are relatively gentle, making them particularly well suited to interacting with sensitive objects such as biological cells. However, at present such systems are used exclusively under manual control by a human operator. This limits the capacity for simultaneous control of multiple microrobots, reducing both experimental throughput and the possibility of cooperative multi-robot operations. In this article, we describe an approach to automated targeting and path planning to enable open-loop control of multiple microrobots. We demonstrate the performance of the method in practice, using microrobots to simultaneously collect, transport and deposit silica microspheres. Using computational simulations based on real microscopic image data, we investigate the capacity of microrobots to collect target cells from within a dissociated tissue culture. Our results indicate the feasibility of using OETdMs to autonomously carry out micromanipulation tasks within complex, unstructured environments.

Authors

Keywords

  • Automation
  • Microscopy
  • Throughput
  • Path planning
  • Visual servoing
  • Resource management
  • Synchronization
  • Target Cells
  • Unstructured Environments
  • Silica Microspheres
  • Work In This Area
  • Maximum Velocity
  • Major Axis
  • Number Of Objects
  • Final Image
  • Target Object
  • Indium Tin Oxide
  • Gaussian Mixture Model
  • Synthetic Images
  • Subventricular Zone
  • Shape Model
  • Task Environment
  • Light Patterns
  • Large Graphs
  • Labeling Density
  • Electric Field Gradient
  • Digital Micromirror Device
  • Adaptive Histogram Equalization
  • Shape Classification
  • Minor Axis Length
  • Task Allocation
  • Free Space
  • Detection Mode
  • Field Of View
  • Volume Constraint
  • Cell Harvesting
  • Micro/Nano Robots
  • Computer Vision for Automation
  • Path Planning for Multiple Mobile Robots or Agents
  • Biological Cell Manipulation

Context

Venue
IEEE/RSJ International Conference on Intelligent Robots and Systems
Archive span
1988-2025
Indexed papers
26578
Paper id
238783458445703219
v2026.09.13