Alexander Antonio Oliva — accepted AI-conference papers

2022

Towards Dynamic Visual Servoing for Interaction Control and Moving Targets

Alexander Antonio Oliva, Erwin Aertbeliën, Joris De Schutter, Paolo Robuffo Giordano, François Chaumette

ICRA 2022poster

In this work we present our results on dynamic visual servoing for the case of moving targets while also exploring the possibility of using such a controller for interaction with the environment. We illustrate the derivation of a feature space impedance controller for tracking a moving object as wel…

Cited by 15 Source ↗Scholar ↗

2021

A General Visual-Impedance Framework for Effectively Combining Vision and Force Sensing in Feature Space

Alexander Antonio Oliva, Paolo Robuffo Giordano, François Chaumette

RA-L 2021

Robotic systems are increasingly used to work in dynamic and/or unstructured environments and to operate with a high degree of safety and autonomy. Consequently, they are often equipped with external sensors capable of perceiving the environment (e.g., cameras) and the contacts that may arise (e.g.

Cited by 22 Source ↗Scholar ↗

2019

Cooperative Visual-Inertial Sensor Fusion: The Analytic Solution

Agostino Martinelli, Alexander Antonio Oliva, Bernard Mourrain

RA-L 2019

This letter analyzes the visual-inertial sensor fusion problem in the cooperative case of two agents, and proves that this sensor fusion problem is equivalent to a simple polynomial equations system that consists of several linear equations and three polynomial equations of second degree. The analyt

Cited by 12 Source ↗Scholar ↗

2019

Dynamic Identification of the Franka Emika Panda Robot With Retrieval of Feasible Parameters Using Penalty-Based Optimization

Claudio Gaz, Marco Cognetti, Alexander Antonio Oliva, Paolo Robuffo Giordano, Alessandro De Luca

RA-L 2019

In this letter, we address the problem of extracting a feasible set of dynamic parameters characterizing the dynamics of a robot manipulator. We start by identifying through an ordinary least squares approach the dynamic coefficients that linearly parametrize the model. From these, we retrieve a set

Cited by 260 Source ↗Scholar ↗