193 citations · 255 across the 17 of their papers we have counts for
17 papers
Sensorless Estimation of Contact Using Deep-Learning for Human-Robot Interaction
Shilin Shan, Quang-Cuong Pham
Physical human-robot interaction has been an area of interest for decades. Collaborative tasks, such as joint compliance, demand high-quality joint torque sensing. While external t…
Real-time Batched Distance Computation for Time-Optimal Safe Path Tracking
Shohei Fujii, Quang-Cuong Pham
In human-robot collaboration, there has been a trade-off relationship between the speed of collaborative robots and the safety of human workers. In our previous paper, we introduce…
Planning Optimal Trajectories for Mobile Manipulators under End-effector Trajectory Continuity Constraint
Quang-Nam Nguyen, Quang-Cuong Pham
Mobile manipulators have been employed in many applications that are traditionally performed by either multiple fixed-base robots or a large robotic system. This capability is enab…
Reinforcement Learning with Parameterized Manipulation Primitives for Robotic Assembly
Nghia Vuong, Quang-Cuong Pham
A common theme in robot assembly is the adoption of Manipulation Primitives as the atomic motion to compose assembly strategy, typically in the form of a state machine or a graph.…
Contact Reduction with Bounded Stiffness for Robust Sim-to-Real Transfer of Robot Assembly
Nghia Vuong, Quang-Cuong Pham
In sim-to-real Reinforcement Learning (RL), a policy is trained in a simulated environment and then deployed on the physical system. The main challenge of sim-to-real RL is to over…
Time-Optimal Path Tracking with ISO Safety Guarantees
Shohei Fujii, Quang-Cuong Pham
One way of ensuring operator's safety during human-robot collaboration is through Speed and Separation Monitoring (SSM), as defined in ISO standard ISO/TS 15066. In general, it is…
Task-Space Clustering for Mobile Manipulator Task Sequencing
Quang-Nam Nguyen, Nicholas Adrian, Quang-Cuong Pham
Mobile manipulators have gained attention for the potential in performing large-scale tasks which are beyond the reach of fixed-base manipulators. The Robotic Task Sequencing Probl…
Adaptive-saturated RNN: Remember more with less instability
Khoi Minh Nguyen-Duy, Quang Pham, Binh T. Nguyen
Orthogonal parameterization is a compelling solution to the vanishing gradient problem (VGP) in recurrent neural networks (RNNs). With orthogonal parameters and non-saturated activ…
Learning for Amalgamation: A Multi-Source Transfer Learning Framework For Sentiment Classification
Cuong V. Nguyen, Khiem H. Le, Anh M. Tran +2
Transfer learning plays an essential role in Deep Learning, which can remarkably improve the performance of the target domain, whose training data is not sufficient. Our work explo…
Time-Optimal Control via Heaviside Step-Function Approximation
Kai Pfeiffer, Quang-Cuong Pham
Least-squares programming is a popular tool in robotics due to its simplicity and availability of open-source solvers. However, certain problems like sparse programming in the $\el…
Geometry-Aware Coverage Path Planning for Depowdering on Complex 3D Surfaces
Van-Thach Do, Quang-Cuong Pham
This paper presents a new approach to obtaining nearly complete coverage paths (CP) with low overlapping on 3D general surfaces using mesh models. The CP is obtained by segmenting…
Fine Robotic Manipulation without Force/Torque Sensor
Shilin Shan, Quang-Cuong Pham
Force Sensing and Force Control are essential to many industrial applications. Typically, a 6-axis Force/Torque (F/T) sensor is mounted between the robot's wrist and the end-effect…
Learning Fast and Slow for Online Time Series Forecasting
Quang Pham, Chenghao Liu, Doyen Sahoo +1
The fast adaptation capability of deep neural networks in non-stationary environments is critical for online time series forecasting. Successful solutions require handling changes…
DFBVS: Deep Feature-Based Visual Servo
Nicholas Adrian, Van-Thach Do, Quang-Cuong Pham
Classical Visual Servoing (VS) rely on handcrafted visual features, which limit their generalizability. Recently, a number of approaches, some based on Deep Neural Networks, have b…
Adaptive Super-twisting Second-order Sliding Mode for Attitude Control of Quadcopter UAVs
Van Truong Hoang, Quang Hieu Pham
This work addresses the modelling and control aspects for quadcopter or drone unmanned aerial vehicles (UAVs). First, the mathematical model of the drone is derived by identifying…
URLNet: Learning a URL Representation with Deep Learning for Malicious URL Detection
Hung Le, Quang Pham, Doyen Sahoo +1
Malicious URLs host unsolicited content and are used to perpetrate cybercrimes. It is imperative to detect them in a timely manner. Traditionally, this is done through the usage of…
Online Deep Learning: Learning Deep Neural Networks on the Fly
Doyen Sahoo, Quang Pham, Jing Lu +1
Deep Neural Networks (DNNs) are typically trained by backpropagation in a batch learning setting, which requires the entire training data to be made available prior to the learning…