Explanipedia

Reasoning and Learning a Perceptual Metric for Self-Training of Reflective Objects in Bin-Picking With a Low-Cost Camera Open

Peiyuan Ni, Chee–Meng Chew, Marcelo H. Ang, Gregory S. Chirikjian · 2025

Bin-picking of metal objects using low-cost RGB-D cameras often suffers from sparse depth information and reflective surface textures, leading to errors and the need for manual labeling. To reduce human intervention, we propose a two-stage…

PRISM: Pointcloud Reintegrated Inference via Segmentation and Cross-attention for Manipulation Open

Daqi Huang, Zhehao Cai, Y Hao, Zechen Li, Chee–Meng Chew · 2025

Robust imitation learning for robot manipulation requires comprehensive 3D perception, yet many existing methods struggle in cluttered environments. Fixed camera view approaches are vulnerable to perspective changes, and 3D point cloud tec…

Rendering Compact Formation and Trajectory Tracking for Cyber Unmanned Ground Vehicles Open

Xiaomin Zhao, Zhengrong Cui, Chee–Meng Chew, Fangfang Dong · 2025

Multi-Robot Reliable Navigation in Uncertain Topological Environments with Graph Attention Networks Open

Zhuoyuan Yu, Hongliang Guo, Albertus Hendrawan Adiwahono, Jianle Chan, Brina Shong Wey Tynn , et al. · 2024

This paper studies the multi-robot reliable navigation problem in uncertain topological networks, which aims at maximizing the robot team's on-time arrival probabilities in the face of road network uncertainties. The uncertainty in these n…

Learning Stable Robot Grasping with Transformer-based Tactile Control Policies Open

En Yen Puang, Zechen Li, Chee–Meng Chew, Shan Luo, Wu Yan · 2024

Measuring grasp stability is an important skill for dexterous robot manipulation tasks, which can be inferred from haptic information with a tactile sensor. Control policies have to detect rotational displacement and slippage from tactile …

Real-Time Terrain Anomaly Perception for Safe Robot Locomotion Using a Digital Double Framework Open

Garen Haddeler, Hari Prasanth Palanivelu, Fabien Colonnier, Yung Ng Chuen, Albertus Hendrawan Adiwahono , et al. · 2023

Real-time Digital Double Framework to Predict Collapsible Terrains for Legged Robots Open

Garen Haddeler, Hari P. Palanivelu, Yung Chuen Ng, Fabien Colonnier, Albertus Hendrawan Adiwahono , et al. · 2022

Inspired by the digital twinning systems, a novel real-time digital double framework is developed to enhance robot perception of the terrain conditions. Based on the very same physical model and motion control, this work exploits the use o…

Traversability analysis with vision and terrain probing for safe legged robot navigation Open

Garen Haddeler, Meng Yee Chuah, Yangwei You, Jianle Chan, Albertus Hendrawan Adiwahono , et al. · 2022

Inspired by human behavior when traveling over unknown terrain, this study proposes the use of probing strategies and integrates them into a traversability analysis framework to address safe navigation on unknown rough terrain. Our framewo…

A Versatile Agent for Fast Learning from Human Instructors Open

Yiwen Chen, Zedong Zhang, Haofeng Liu, Jiayi Tan, Chee–Meng Chew , et al. · 2022

In recent years, a myriad of superlative works on intelligent robotics policies have been done, thanks to advances in machine learning. However, inefficiency and lack of transfer ability hindered algorithms from pragmatic applications, esp…

Effects of root chord movement on thrust generation of oscillatory pectoral fins Open

Soheil Arastehfar, Chee–Meng Chew · 2020

Fin kinematics is the key to thrust generation of oscillatory pectoral fins of manta rays. This could be one of the main reasons that fin designs of robotic manta rays are becoming more complex to simulate the fin kinematics more closely s…

PointAtrousGraph: Deep Hierarchical Encoder-Decoder with Atrous Convolution for Point Clouds. Open

Liang Pan, Chee–Meng Chew, Gim Hee Lee · 2019

PointAtrousGraph: Deep Hierarchical Encoder-Decoder with Point Atrous Convolution for Unorganized 3D Points Open

Liang Pan, Chee–Meng Chew, Gim Hee Lee · 2019

Motivated by the success of encoding multi-scale contextual information for image analysis, we propose our PointAtrousGraph (PAG) - a deep permutation-invariant hierarchical encoder-decoder for efficiently exploiting multi-scale edge featu…

Edge and Corner Detection for Unorganized 3D Point Clouds with Application to Robotic Welding Open

Syeda Mariam Ahmed, Yan Zhi Tan, Chee–Meng Chew, Abdullah Al Mamun, Fook Seng Wong · 2018

In this paper, we propose novel edge and corner detection algorithms for unorganized point clouds. Our edge detection method evaluates symmetry in a local neighborhood and uses an adaptive density based threshold to differentiate 3D edge p…

Pixel and Feature Level Based Domain Adaption for Object Detection in Autonomous Driving Open

Yuhu Shan, Wen Feng Lu, Chee–Meng Chew · 2018

Annotating large scale datasets to train modern convolutional neural networks is prohibitively expensive and time-consuming for many real tasks. One alternative is to train the model on labeled synthetic datasets and apply it in the real s…

Object Detection and Motion Planning for Automated Welding of Tubular\n Joints Open

Syeda Mariam Ahmed, Yan Zhi Tan, Gim Hee Lee, Chee–Meng Chew, Chee Khiang Pang · 2018

Automatic welding of tubular TKY joints is an important and challenging task\nfor the marine and offshore industry. In this paper, a framework for tubular\njoint detection and motion planning is proposed. The pose of the real tubular\njoin…

Object Detection and Motion Planning for Automated Welding of Tubular Joints Open

Syeda Mariam Ahmed, Yan Zhi Tan, Gim Hee Lee, Chee–Meng Chew, Chee Khiang Pang · 2018

Automatic welding of tubular TKY joints is an important and challenging task for the marine and offshore industry. In this paper, a framework for tubular joint detection and motion planning is proposed. The pose of the real tubular joint i…

Edge and Corner Detection for Unorganized 3D Point Clouds with\n Application to Robotic Welding Open

Syeda Mariam Ahmed, Yan Zhi Tan, Chee–Meng Chew, Abdullah Al Mamun, Fook Seng Wong · 2018

In this paper, we propose novel edge and corner detection algorithms for\nunorganized point clouds. Our edge detection method evaluates symmetry in a\nlocal neighborhood and uses an adaptive density based threshold to\ndifferentiate 3D edg…

Smooth and Efficient Policy Exploration for Robot Trajectory Learning Open

Shidi Li, Chee–Meng Chew, Velusamy Subramaniam · 2018

Many policy search algorithms have been proposed for robot learning and proved to be practical in real robot applications. However, there are still hyperparameters in the algorithms, such as the exploration rate, which requires manual tuni…

Application of deep neural network in estimation of the weld bead parameters Open

Soheil Keshmiri, Xin Zheng, Chee–Meng Chew, Chee Khiang Pang · 2015

We present a deep learning approach to estimation of the bead parameters in welding tasks. Our model is based on a four-hidden-layer neural network architecture. More specifically, the first three hidden layers of this architecture utilize…

Application of Deep Neural Network in Estimation of the Weld Bead\n Parameters Open

Soheil Keshmiri, Xin Zheng, Chee–Meng Chew, Chee Khiang Pang · 2015

We present a deep learning approach to estimation of the bead parameters in\nwelding tasks. Our model is based on a four-hidden-layer neural network\narchitecture. More specifically, the first three hidden layers of this\narchitecture util…

An Adaptive Sampling Approach to 3D Reconstruction of Weld Joint Open

Soheil Keshmiri, Syeda Mariam Ahmed, Yue Wu, Chee–Meng Chew, Chee Khiang Pang · 2015

We present an adaptive sampling approach to 3D reconstruction of the welding joint using the point cloud that is generated by a laser sensor. We start with a randomized strategy to approximate the surface of the volume of interest through …

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