activity
20172023
most citedOnline Deep Learning: Learning Deep Neural Networks on the Fly

5 citations · 6 across the 6 of their papers we have counts for

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10 papers · 1 filter

cs.RO2023

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…

cs.RO2023

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…

cs.RO2023

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…

cs.RO2023

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.…

cs.RO2023

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…

cs.RO2023

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…