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Jérôme Truc

dblp:324/6244 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2022
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Systems, architecture and hardware · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Planning, search and constraint satisfaction · 56% Motion planning and robot control · 28% Legged, aerial and field robots · 17%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › robot task planning
human-aware planning
0.612022
KHAOS: a Kinematic Human Aware Optimization-based System for Reactive Planning of Flying-Coworker · ICRA 2022
Robotics › Motion planning and robot control
motion planning
0.612022
KHAOS: a Kinematic Human Aware Optimization-based System for Reactive Planning of Flying-Coworker · ICRA 2022
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
reactive planning
0.612022
KHAOS: a Kinematic Human Aware Optimization-based System for Reactive Planning of Flying-Coworker · ICRA 2022
Robotics › Legged, aerial and field robots
aerial robots
0.212022
KHAOS: a Kinematic Human Aware Optimization-based System for Reactive Planning of Flying-Coworker · ICRA 2022
Robotics › Legged, aerial and field robots › aerial robots
drone navigation
0.212022
KHAOS: a Kinematic Human Aware Optimization-based System for Reactive Planning of Flying-Coworker · ICRA 2022

Methods — techniques the papers use, named apart from their topics

stochastic optimization · 0.6
YearPublicationVenuePosition
2022 KHAOS: a Kinematic Human Aware Optimization-based System for Reactive Planning of Flying-Coworker
abstract
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 reactive planner based on stochastic optimization for drone navigation. Besides considering the kinematics constraints of the drone, we propose two criteria to produce socially acceptable trajectories. The first, called discomfort, considers the unease caused to the humans spatially close to fast-moving drones. The second, called visibility, promotes the drone's visibility for humans. We demonstrate the planner's performance and adaptability in various simulated experiments.
Jérôme Truc, Phani-Teja Singamaneni, Daniel Sidobre, Serena Ivaldi, Rachid Alami 0001
ICRA1