June 2023

We apply IoT technologies to implement automatic abnormal event detection and E-clinical cart information systems for long-term care institutions. The E-clinical cart can follow medical personnel, and therefore it eases the physical workload of manually pushing the clinical cart. For autonomous patrol work, using the proposed human action recognition with few-shot data, some abnormal actions, such as falls and squats, can be detected. Moreover, the proposed monitoring platform with a graphical user interface can improve the E-quality and efficiency of nursing works. The experimental results show that the intelligent data monitoring system can effectively carry out the task assignment of the E-clinical cart and event monitoring and warning in long-term care institutions.

March 2022

This paper presents a learning from demonstration (LfD) robotic system to provide a more intuitive way for robots to efficiently perform tasks through learning from human demonstration on the basis of two major components: understanding through human demonstration and reproduction by robot arm. To understand the human demonstration, we propose a vision-based spatial-temporal action detection method to detect human actions that focuses on meticulous hand movement in real-time to establish an action base. An object trajectory inductive method is then proposed to obtain a key path for objects manipulated by the human through multiple demonstrations. In robot reproduction, we integrate the sequence of actions in the action base and the key path derived by the object trajectory inductive method for motion planning to reproduce the task demonstrated by the human user. Because of the capability of learning from demonstration, the robot can reproduce the tasks that the human demonstrated via vision sensors in unseen contexts.

Aug. 2018

A big wave of AI has arrived with increasing demands for chips low in voltage and energy consumption. The technology is still in early development, but it has the potential to become a big business chance for Taiwan’s semiconductor-related industries. Profs. Wang Wei-Yen, Chen-Chien James Hsu and Chia-Hung Yeh of National Taiwan Normal University have developed innovative design concepts and application frameworks of AI, which are applied by AVSdsp into its wafer design system. The end product is an AI chip nicknamed Mipy, smaller than one square centimeter and is the world’s smallest.

Sept. 2017

We develop an automatic egg-inspection system which can grip fragile eggs and identify the freshness of eggs. In the hardware architecture, we utilize the proposed serial-parallel robotic arm, two pressure sensors, one electronic balance, and three webcams. The pressure sensors on the gripper make the robotic arm to grip fragile things without breaking them. The proposed system combines advantages of serial robotic arms and traditional delta robots.

Dec. 2016

An autonomous mobility controller to perform a stair-climbing task for a tracked robot is proposed. Five modes were designed to autonomously explore and climb stairs using only depth information captured by a Kinect sensor. These modes have the advantage of smoothly and safely guiding the tracked robot to complete its tasks.