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Daniele Nardi

13 accepted papers

2026

Context Matters! Relaxing Goals with LLMs for Feasible 3D Scene Planning

Emanuele Musumeci, Michele Brienza, Francesco Argenziano, Abdel Hakim Drid, Vincenzo Suriani, Daniele Nardi +1
ICRA 2026poster

Embodied agents need to plan and act reliably in real and complex 3D environments. Classical planning (e.g., PDDL) offers structure and guarantees, but in practice it fails under noisy perception and incorrect predicate grounding. On the other hand, Large Language Models (LLMs)-based planners levera…

Cited by 0Source ↗PDF ↗Scholar ↗
2026

To Harvest or Not to Harvest: Mapping and Decision-Making for a Selective Table Grape Harvesting Robot

Ruben Beumer, Leonardo Saraceni, Daniele Nardi, Duarte Antunes, René Molengraft van de, Thomas Ciarfuglia
ICRA 2026poster

This letter focuses on robotic harvesting of delicate crops such as table grapes, featuring selective harvesting based on individual product properties. The robot detects grape bunches and estimates their positions and quality attributes. However, sensor limitations and occlusions affect data comple…

Cited by 0Source ↗Scholar ↗
2024

AgriSORT: A Simple Online Real-time Tracking-by-Detection framework for robotics in precision agriculture

Leonardo Saraceni, Ionut M. Motoi, Daniele Nardi, Thomas A. Ciarfuglia
ICRA 2024poster

The problem of multi-object tracking (MOT) consists in detecting and tracking all the objects in a video sequence while keeping a unique identifier for each object. It is a challenging and fundamental problem for robotics. In precision agriculture the challenge of achieving a satisfactory solution i…

Cited by 10Source ↗code ↗Scholar ↗
2024

EMPOWER: Embodied Multi-role Open-vocabulary Planning with Online Grounding and Execution

Francesco Argenziano, Michele Brienza, Vincenzo Suriani, Daniele Nardi, Domenico D. Bloisi
IROS 2024poster

Task planning for robots in real-life settings presents significant challenges. These challenges stem from three primary issues: the difficulty in identifying grounded sequences of steps to achieve a goal; the lack of a standardized mapping between high-level actions and low-level commands; and the…

Cited by 1Source ↗Scholar ↗
2022

Optimizing Demonstrated Robot Manipulation Skills for Temporal Logic Constraints

Akshay Dhonthi, Philipp Schillinger, Leonel Rozo, Daniele Nardi
IROS 2022poster

For performing robotic manipulation tasks, the core problem is determining suitable trajectories that fulfill the task requirements. Various approaches to compute such trajectories exist, being learning and optimization the main driving techniques. Our work builds on the learning-from-demonstration…

Cited by 8Source ↗Scholar ↗
2020

Explainable Inference on Sequential Data via Memory-Tracking

Biagio La Rosa, Roberto Capobianco, Daniele Nardi
IJCAI 2020poster

In this paper we present a novel mechanism to get explanations that allow to better understand network predictions when dealing with sequential data. Specifically, we adopt memory-based networks — Differential Neural Computers — to exploit their capability of storing data in memory and reusin…

Cited by 0Source ↗PDF ↗code ↗Scholar ↗
2019

AgriColMap: Aerial-Ground Collaborative 3D Mapping for Precision Farming

Ciro Potena, Raghav Khanna, Juan I. Nieto, Roland Siegwart, Daniele Nardi, Alberto Pretto
RA-L 2019

The combination of aerial survey capabilities of unmanned aerial vehicles (UAVs) with targeted intervention abilities of agricultural unmanned ground vehicles (UGVs) can significantly improve the effectiveness of robotic systems applied to precision agriculture. In this context, building and updatin

Cited by 81Source ↗Scholar ↗
2018

An Effective Multi-Cue Positioning System for Agricultural Robotics

Marco Imperoli, Ciro Potena, Daniele Nardi, Giorgio Grisetti, Alberto Pretto
RA-L 2018

The self-localization capability is a crucial component for Unmanned Ground Vehicles in farming applications. Approaches based solely on visual cues or on a low-cost Global Positioning System (GPS) are easily prone to fail in such scenarios. In this letter, we present a robust and accurate three-dim

Cited by 41Source ↗Scholar ↗
2016

Multi-robot search for a moving target: Integrating world modeling, task assignment and context

Francesco Riccio, Emanuele Borzi, Guglielmo Gemignani, Daniele Nardi
IROS 2016poster

In this paper, we address coordination within a team of cooperative autonomous robots that need to accomplish a common goal. Our survey of the vast literature on the subject highlights two directions to further improve the performance of a multi-robot team. In particular, in a dynamic environment, c…

Cited by 18Source ↗Scholar ↗
2015

Explicit representation of social norms for social robots

Fabio Maria Carlucci, Lorenzo Nardi, Luca Iocchi, Daniele Nardi
IROS 2015poster

As robots are expected to become more and more available in everyday environments, interaction with humans is assuming a central role. Robots working in populated environments are thus expected to demonstrate socially acceptable behaviors and to follow social norms. However, most of the recent works…

Cited by 48Source ↗Scholar ↗
2015

Multi-robot task acquisition through sparse coordination

Steven D. Klee, Guglielmo Gemignani, Daniele Nardi, Manuela Veloso
IROS 2015poster

In this paper, we consider several autonomous robots with separate tasks that require coordination, but not a coupling at every decision step. We assume that each robot separately acquires its task, possibly from different providers. We address the problem of multiple robots incrementally acquiring…

Cited by 8Source ↗Scholar ↗