2 citations · 3 across the 11 of their papers we have counts for
11 papers
GNN-based Decentralized Perception in Multirobot Systems for Predicting Worker Actions
Ali Imran, Giovanni Beltrame, David St-Onge
In industrial environments, predicting human actions is essential for ensuring safe and effective collaboration between humans and robots. This paper introduces a perception framew…
LiDAR-based Real-Time Object Detection and Tracking in Dynamic Environments
Wenqiang Du, Giovanni Beltrame
In dynamic environments, the ability to detect and track moving objects in real-time is crucial for autonomous robots to navigate safely and effectively. Traditional methods for dy…
Variable Time Step Reinforcement Learning for Robotic Applications
Dong Wang, Giovanni Beltrame
Traditional reinforcement learning (RL) generates discrete control policies, assigning one action per cycle. These policies are usually implemented as in a fixed-frequency control…
MOSEAC: Streamlined Variable Time Step Reinforcement Learning
Dong Wang, Giovanni Beltrame
Traditional reinforcement learning (RL) methods typically employ a fixed control loop, where each cycle corresponds to an action. This rigidity poses challenges in practical applic…
Learning Control Barrier Functions and their application in Reinforcement Learning: A Survey
Maeva Guerrier, Hassan Fouad, Giovanni Beltrame
Reinforcement learning is a powerful technique for developing new robot behaviors. However, typical lack of safety guarantees constitutes a hurdle for its practical application on…
From the Lab to the Theater: An Unconventional Field Robotics Journey
Ali Imran, Vivek Shankar Varadharajan, Rafael Gomes Braga +6
Artistic performances involving robotic systems present unique technical challenges akin to those encountered in other field deployments. In this paper, we delve into the orchestra…