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Jyh-Ming Lien

15 accepted papers

2021

Learning to Herd Agents Amongst Obstacles: Training Robust Shepherding Behaviors Using Deep Reinforcement Learning

RA-L 2021

Robotic shepherding problem considers the control and navigation of a group of coherent agents (e.g., a flock of bird or a fleet of drones) through the motion of an external robot, called shepherd. Machine learning based methods have successfully solved this problem in an environment with no obstacl

Cited by 35SourceScholar
2021

Planning Laser-Forming Folding Motion with Thermal Simulation

ICRA 2021poster

Designing a robot or structure that can fold into a target shape is a process that involves challenges originated from multiple sources. For example, the designer of self-folding robots must consider foldability from geometric and kinematic aspects to avoid self-collisions and undesired deformations…

Cited by 1SourceScholar
2019

Computing 3-D From-Region Visibility Using Visibility Integrity

RA-L 2019

Visibility integrity (VI) is a measurement of similarity between the visibilities of regions. It can be used to approximate the visibility of coherently moving targets, called group visibility. It has been shown that computing visibility integrity using agglomerative clustering takes O(n4 log n) for

Cited by 3SourceScholar
2017

Material Editing Using a Physically Based Rendering Network

ICCV 2017spotlight

The ability to edit materials of objects in images is desirable by many content creators. However, this is an extremely challenging task as it requires to disentangle intrinsic physical properties of an image. We propose an end-to-end network architecture that replicates the forward image formation…

Cited by 105PDFScholar