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Ching-I Huang

5 accepted papers

2024

An Evaluation Framework of Human-Robot Teaming for Navigation Among Movable Obstacles via Virtual Reality-Based Interactions

RA-L 2024

Robots are essential for tasks that are hazardous or beyond human capabilities. However, the results of the Defense Advanced Research Projects Agency (DARPA) Subterranean (SubT) Challenge revealed that despite various techniques for robot autonomy, human input is still required in some complex situa

Cited by 5SourceScholar
2023

Fed-HANet: Federated Visual Grasping Learning for Human Robot Handovers

RA-L 2023

Human-robot handover is a key capability of service robots, such as those used to perform routine logistical tasks for healthcare workers. Recent algorithms have achieved tremendous advances in object-agnostic end-to-end planar grasping with up to six degrees of freedom (DoF); however, compiling the

Cited by 11SourcecodeScholar
2023

Towards More Efficient EfficientDets and Real-Time Marine Debris Detection

RA-L 2023

Marine debris is a problem both for the health of marine environments and for the human health since tiny pieces of plastic called “microplastics” resulting from the debris decomposition over the time are entering the food chain at any levels. For marine debris detection and removal, autonomous unde

Cited by 35SourceScholar
2022

WFH-VR: Teleoperating a Robot Arm to set a Dining Table across the Globe via Virtual Reality

IROS 2022poster

This paper presents an easy-to-deploy, virtual reality-based teleoperation system for controlling a robot arm. The proposed system is based on a consumer-grade virtual reality device (Oculus Quest 2) with a low-cost robot arm (a LoCoBot) to allow easy replication and set up. The proposed Work-from-H…

Cited by 22SourcecodeScholar
2021

Cross-Modal Contrastive Learning of Representations for Navigation Using Lightweight, Low-Cost Millimeter Wave Radar for Adverse Environmental Conditions

RA-L 2021

Deep reinforcement learning (RL), where the agent learns from mistakes, has been successfully applied to a variety of tasks. With the aim of learning collision-free policies for unmanned vehicles, deep RL has been used for training with various types of data, such as colored images, depth images, an

Cited by 23SourcecodeScholar