activity
20212026
most citedA Hybrid Learning and Optimization Framework to Achieve Physically Interactive Tasks with Mobile Manipulators

41 citations · 60 across the 8 of their papers we have counts for

collaborators

8 papers

eess.SY2026

Bridging Reinforcement Learning and Optimal Control via Feasible Action Mapping

Stefan Richter, Alberto Giammarino, Guillem Torrente +2

Operating constrained dynamical systems requires controllers to efficiently solve complex tasks while enforcing recursive feasibility and safety constraints. To address these compe…

cs.RO2023★ 1 cited

A Reinforcement Learning Approach for Robotic Unloading from Visual Observations

Vittorio Giammarino, Alberto Giammarino, Matthew Pearce

In this work, we focus on a robotic unloading problem from visual observations, where robots are required to autonomously unload stacks of parcels using RGB-D images as their prima…

cs.RO2022

An Open Tele-Impedance Framework to Generate Data for Contact-Rich Tasks in Robotic Manipulation

Alberto Giammarino, Juan M. Gandarias, Arash Ajoudani

Using large datasets in machine learning has led to outstanding results, in some cases outperforming humans in tasks that were believed impossible for machines. However, achieving…

cs.RO2022★ 2 cited

An Object Deformation-Agnostic Framework for Human-Robot Collaborative Transportation

Doganay Sirintuna, Alberto Giammarino, Arash Ajoudani

In this study, an adaptive object deformability-agnostic human-robot collaborative transportation framework is presented. The proposed framework enables to combine the haptic infor…

cs.RO2022★ 41 cited

A Hybrid Learning and Optimization Framework to Achieve Physically Interactive Tasks with Mobile Manipulators

Jianzhuang Zhao, Alberto Giammarino, Edoardo Lamon +3

This paper proposes a hybrid learning and optimization framework for mobile manipulators for complex and physically interactive tasks. The framework exploits an admittance-type phy…

cs.RO2022★ 1 cited

Human-Robot Collaborative Carrying of Objects with Unknown Deformation Characteristics

Doganay Sirintuna, Alberto Giammarino, Arash Ajoudani

In this work, we introduce an adaptive control framework for human-robot collaborative transportation of objects with unknown deformation behaviour. The proposed framework takes as…