activity
20162026
most citedThe Impacts of Human-Cobot Collaboration on Perceived Cognitive Load and Usability during an Industrial Task: An Exploratory Experiment

47 citations · 139 across the 31 of their papers we have counts for

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24 papers · 1 filter

cs.AI2026

Towards Numerical TOHTN Planning with SMT-based HTN-SAT Encoding

Gaspard Quenard, Takudzwa Togarepi, Damien Pellier +1

While HTN planning has received significant attention in recent years, support for numerical reasoning remains very limited. In this paper, we investigate numerical Totally-Ordered…

cs.AI2026

Lose the Order, Keep the Hierarchy: Deordering HTN Plans

Takudzwa Togarepi, Gaspard Quenard, Damien Pellier +1

Hierarchical Task Network (HTN) planning is a powerful planning formalism based on task decomposition. Although most of the literature studied plan generation, comparatively less a…

cs.AI2026

A complementary study on PlanGPT: Evaluation with defined Performance Metrics and comparison with a planner

Youssef Abdelkader, Humbert Fiorino, Damien Pellier

Automated Planning is a subfield of Artificial Intelligence (AI) where the main objective is generating a sequence of actions, known as a plan, that helps us reach a goal state fro…

cs.AI2024★ 2 cited

SibylSat: Using SAT as an Oracle to Perform a Greedy Search on TOHTN Planning

Gaspard Quenard, Damier Pellier, Humbert Fiorino

This paper presents SibylSat, a novel SAT-based method designed to efficiently solve totally-ordered HTN problems (TOHTN). In contrast to prevailing SAT-based HTN planners that emp…

cs.AI2024★ 26 cited

Human-Cobot collaboration's impact on success, time completion, errors, workload, gestures and acceptability during an assembly task

Étienne Fournier, Christine Jeoffrion, Belal Hmedan +3

The 5.0 industry promotes collaborative robots (cobots). This research studies the impacts of cobot collaboration using an experimental setup. 120 participants realized a simple an…

cs.AI2023

On Guiding Search in HTN Temporal Planning with non Temporal Heuristics

Nicolas Cavrel, Damien Pellier, Humbert Fiorino

The Hierarchical Task Network (HTN) formalism is used to express a wide variety of planning problems as task decompositions, and many techniques have been proposed to solve them. H…

cs.AI2023★ 1 cited

HDDL 2.1: Towards Defining a Formalism and a Semantics for Temporal HTN Planning

Damien Pellier, Alexandre Albore, Humbert Fiorino +1

Real world applications as in industry and robotics need modelling rich and diverse automated planning problems. Their resolution usually requires coordinated and concurrent action…

cs.AI2022

An Efficient HTN to STRIPS Encoding for Concurrent Plans

N. Cavrel, D. Pellier, H. Fiorino

The Hierarchical Task Network (HTN) formalism is used to express a wide variety of planning problems in terms of decompositions of tasks into subtaks. Many techniques have been pro…

cs.AI2022★ 1 cited

An Accurate HDDL Domain Learning Algorithm from Partial and Noisy Observations

M. Grand, H. Fiorino, D. Pellier

The Hierarchical Task Network ({\sf HTN}) formalism is very expressive and used to express a wide variety of planning problems. In contrast to the classical {\sf STRIPS} formalism…

cs.AI2022

HDDL 2.1: Towards Defining an HTN Formalism with Time

D. Pellier, H. Fiorino, M. Grand +2

Real world applications of planning, like in industry and robotics, require modelling rich and diverse scenarios. Their resolution usually requires coordinated and concurrent actio…

cs.AI2021

TempAMLSI : Temporal Action Model Learning based on Grammar Induction

Maxence Grand, Damien Pellier, Humbert Fiorino

Hand-encoding PDDL domains is generally accepted as difficult, tedious and error-prone. The difficulty is even greater when temporal domains have to be encoded. Indeed, actions hav…

cs.AI2021★ 2 cited

From Classical to Hierarchical: benchmarks for the HTN Track of the International Planning Competition

Damien Pellier, Humbert Fiorino

In this short paper, we outline nine classical benchmarks submitted to the first hierarchical planning track of the International Planning competition in 2020. All of these benchma…

cs.AI2020★ 6 cited

Totally and Partially Ordered Hierarchical Planners in PDDL4J Library

Damien Pellier, Humbert Fiorino

In this paper, we outline the implementation of the TFD (Totally Ordered Fast Downward) and the PFD (Partially ordered Fast Downward) hierarchical planners that participated in the…

cs.AI2020★ 2 cited

AMLSI: A Novel Accurate Action Model Learning Algorithm

Maxence Grand, Humbert Fiorino, Damien Pellier

This paper presents new approach based on grammar induction called AMLSI Action Model Learning with State machine Interactions. The AMLSI approach does not require a training datas…

cs.AI2019★ 10 cited

HDDL -- A Language to Describe Hierarchical Planning Problems

D. Höller, G. Behnke, P. Bercher +4

The research in hierarchical planning has made considerable progress in the last few years. Many recent systems do not rely on hand-tailored advice anymore to find solutions, but a…

cs.AI2019★ 5 cited

Hierarchical Planning in the IPC

D. Höller, G. Behnke, P. Bercher +4

Over the last year, the amount of research in hierarchical planning has increased, leading to significant improvements in the performance of planners. However, the research is dive…

cs.AI2018

A Review on Learning Planning Action Models for Socio-Communicative HRI

Ankuj Arora, Humbert Fiorino, Damien Pellier +1

For social robots to be brought more into widespread use in the fields of companionship, care taking and domestic help, they must be capable of demonstrating social intelligence. I…

cs.AI2018

Mean-based Heuristic Search for Real-Time Planning

Damien Pellier, Bruno Bouzy, Marc Métivier

In this paper, we introduce a new heuristic search algorithm based on mean values for real-time planning, called MHSP. It consists in associating the principles of UCT, a bandit-ba…

cs.AI2018

Mining useful Macro-actions in Planning

Sandra Castellanos-Paez, Damien Pellier, Humbert Fiorino +1

Planning has achieved significant progress in recent years. Among the various approaches to scale up plan synthesis, the use of macro-actions has been widely explored. As a first s…

cs.AI2018★ 3 cited

A Framework for Robot Programming in Cobotic Environments: First user experiments

Ying Siu Liang, Damien Pellier, Humbert Fiorino +1

The increasing presence of robots in industries has not gone unnoticed. Large industrial players have incorporated them into their production lines, but smaller companies hesitate…

cs.AI2018

Coordinated exploration for labyrinthine environments with application to the Pursuit-Evasion problem

Damien Pellier, Humbert Fiorino

This paper introduces a multirobot cooperation approach to solve the "pursuit evasion" problem for mobile robots that have omnidirectional vision sensors. The main characteristic o…

cs.AI2018

Assumption-Based Planning

Damien Pellier, Humbert Fiorino

The purpose of the paper is to introduce a new approach of planning called Assumption-Based Planning. This approach is a very interesting way to devise a planner based on a multi-a…

cs.AI2018★ 1 cited

Action Model Acquisition using LSTM

Ankuj Arora, Humbert Fiorino, Damien Pellier +1

In the field of Automated Planning and Scheduling (APS), intelligent agents by virtue require an action model (blueprints of actions whose interleaved executions effectuates transi…

cs.AI2016

Learning Macro-actions for State-Space Planning

Sandra Castellanos-Paez, Damien Pellier, Humbert Fiorino +1

Planning has achieved significant progress in recent years. Among the various approaches to scale up plan synthesis, the use of macro-actions has been widely explored. As a first s…