Abstract-Micromanipulation systems have recently been receiving increased attention. Tele-operated or automated micromanipulation is a challenging task due to the need for high-frequency position or force feedback to guarantee stability. In addition, the integration of sensors within micromanipulation platforms is complex. Vision is a commonly used solution for sensing; unfortunately the update rate of the frame-based acquisition process of current available cameras can not ensure-at reasonable costs-stable automated or tele-operated control at the microscale level, where low inertia produces highly unreachable dynamic phenomena. This paper presents a novel vision-based microrobotic system combining both an asynchronous Address Event Representation (AER) silicon retina and a conventional frame-based camera. Unlike frame-based cameras, recent artificial retinas transmit their outputs as a continuous stream of asynchronous temporal events, in a manner similar to the output cells of a biological retina, enabling high update rates. This paper introduces an Event-based Iterative Closest Point algorithm to track a microgripper's position at a frequency of 4 kHz. The temporal precision of the asynchronous silicon retina is used to provide a haptic feedback to assist users during manipulation tasks, whereas the frame-based camera is used to retrieve the position of the object that must be manipulated. This paper presents the results of an experiment on tele-operating a sphere of diameter around 50 µm using a piezo-electric gripper in a pick-and-place task.
In REF , the events in a sliding window of fixed duration were selected as input of an Iterative Closest Point (ICP) algorithm that was used to guide a micro gripper to grasp an object with a mean update rate of 4 kHz.
Asynchronous Event-Based Visual Shape Tracking for Stable Haptic Feedback in Microrobotics
IEEE Transactions on Robotics
IEEE Transactions on Robotics
Mathematics Computer Science