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Serena Ivaldi

17 accepted papers

2023

Learning Height for Top-Down Grasps with the DIGIT Sensor

ICRA 2023poster

We address the problem of grasping unknown objects identified from top-down images with a parallel gripper. When no object 3D model is available, the state-of-the-art grasp generators identify the best candidate locations for planar grasps using the RGBD image. However, while they generate the Carte…

Cited by 1SourceScholar
2022

Data-efficient learning of object-centric grasp preferences

ICRA 2022poster

Grasping made impressive progress during the last few years thanks to deep learning. However, there are many objects for which it is not possible to choose a grasp by only looking at an RGB-D image, might it be for physical reasons (e.g., a hammer with uneven mass distribution) or task constraints (…

Cited by 7SourceScholar
2022

First Do Not Fall: Learning to Exploit a Wall With a Damaged Humanoid Robot

RA-L 2022

Humanoid robots could replace humans in hazardous situations but most of such situations are equally dangerous for them, which means that they have a high chance of being damaged and falling. We hypothesize that humanoid robots would be mostly used in buildings, which makes them likely to be close t

Cited by 6SourcecodeScholar
2022

KHAOS: a Kinematic Human Aware Optimization-based System for Reactive Planning of Flying-Coworker

ICRA 2022poster

The use of drones in human-populated areas is increasing day by day. Such robots flying in close proximity to humans and potentially interacting with them, as in object handover or delivery, need to carefully plan their navigation considering the presence of humans. We propose a humanaware 3D reacti…

Cited by 9SourceScholar
2022

Multi-Objective Trajectory Optimization to Improve Ergonomics in Human Motion

RA-L 2022

Work-related musculoskeletal disorders are a major health issue often caused by awkward postures. Identifying and recommending more ergonomic body postures requires optimizing the worker’s motion with respect to ergonomics criteria based on the human kinematic/kinetic state. However, many ergonomics

Cited by 18SourceScholar
2021

Autonomy in Physical Human-Robot Interaction: A Brief Survey

RA-L 2021

Sharing the control of a robotic system with an autonomous controller allows a human to reduce his/her cognitive and physical workload during the execution of a task. In recent years, the development of inference and learning techniques has widened the spectrum of applications of shared control (SC)

Cited by 193SourceScholar
2021

Human Posture Prediction During Physical Human-Robot Interaction

RA-L 2021

When a human is interacting physically with a robot to accomplish a task, his/her posture is inevitably influenced by the robot movement. Since the human is not controllable, an active robot imposing a collaborative trajectory should predict the most likely human posture. This prediction should cons

Cited by 30SourceScholar
2020

Learning Robust Task Priorities and Gains for Control of Redundant Robots

RA-L 2020

Generating complex movements in redundant robots like humanoids is usually done by means of multi-task controllers based on quadratic programming, where a multitude of tasks is organized according to strict or soft priorities. Time-consuming tuning and expertise are required to choose suitable task

Cited by 15SourceScholar
2019

Activity Recognition for Ergonomics Assessment of Industrial Tasks With Automatic Feature Selection

RA-L 2019

In industry, ergonomic assessment is currently performed manually based on the identification of postures and actions by experts. We aim at proposing a system for automatic ergonomic assessment based on activity recognition. In this letter, we define a taxonomy of activities, composed of four levels

Cited by 52SourceScholar
2018

Generating Assistive Humanoid Motions for Co-Manipulation Tasks with a Multi-Robot Quadratic Program Controller

ICRA 2018poster

Human-humanoid collaborative tasks require that the robot take into account the goals of the task, interaction forces with the human, and its own balance. We present a formulation for a real-time humanoid controller which allows the robot to keep itself balanced, while also assisting the human in ac…

Cited by 26SourceScholar
2018

The CoDyCo Project Achievements and Beyond: Toward Human Aware Whole-Body Controllers for Physical Human Robot Interaction

RA-L 2018

The success of robots in real-world environments is largely dependent on their ability to interact with both humans and said environment. The FP7 EU project CoDyCo focused on the latter of these two challenges by exploiting both rigid and compliant contacts dynamics in the robot control problem. Reg

Cited by 32SourceScholar
2016

Learning soft task priorities for control of redundant robots

ICRA 2016poster

One of the key problems in planning and control of redundant robots is the fast generation of controls when multiple tasks and constraints need to be satisfied. In the literature, this problem is classically solved by multi-task prioritized approaches, where the priority of each task is determined b…

Cited by 44SourceScholar
2015

Inertial parameters identification and joint torques estimation with proximal force/torque sensing

ICRA 2015poster

Classically robot force control passes through joint torques measurement or estimation. Within this context, classical torque sensing technologies rely on current sensing on motor windings and on torsion sensing on motor shaft. An alternative approach was recently proposed in [1] and combines whole-…

Cited by 20SourceScholar
2015

Learning inverse dynamics models with contacts

ICRA 2015poster

In whole-body control, joint torques and external forces need to be estimated accurately. In principle, this can be done through pervasive joint-torque sensing and accurate system identification. However, these sensors are expensive and may not be integrated in all links. Moreover, the exact positio…

Cited by 67SourceScholar