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Noah Franceschini

dblp:387/9750 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
—ORCID · none

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
Motion planning and robot control · 60% Legged, aerial and field robots · 40%

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

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot control › contact control › contact task control › robot force control
adaptive impedance control
0.912025
Autonomous Excavation of Challenging Terrain using Oscillatory Primitives and Adaptive Impedance Control · ICRA 2025
Robotics › Legged, aerial and field robots › construction robotics
autonomous excavation
0.912025
Autonomous Excavation of Challenging Terrain using Oscillatory Primitives and Adaptive Impedance Control · ICRA 2025
Robotics › Legged, aerial and field robots › construction robotics
excavation
0.912025
Autonomous Excavation of Challenging Terrain using Oscillatory Primitives and Adaptive Impedance Control · ICRA 2025
Robotics › Motion planning and robot control › robot control
impedance control
0.912025
Autonomous Excavation of Challenging Terrain using Oscillatory Primitives and Adaptive Impedance Control · ICRA 2025
Robotics › Motion planning and robot control
robot control
0.912025
Autonomous Excavation of Challenging Terrain using Oscillatory Primitives and Adaptive Impedance Control · ICRA 2025

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

reactive attractor impedance control · 0.9oscillatory motion primitives · 0.9
YearPublicationVenuePosition
2025 Autonomous Excavation of Challenging Terrain using Oscillatory Primitives and Adaptive Impedance Control
abstract
This paper addresses the challenge of autonomous excavation of challenging terrains, in particular those that are prone to jamming and inter-particle adhesion when tackled by a standard penetrate-drag-scoop motion pattern. Inspired by human excavation strategies, our approach incorporates oscillatory rotation elements - including swivel, twist, and dive motions - to break up compacted, tangled grains and reduce jamming. We also present an adaptive impedance control method, the Reactive Attractor Impedance Controller (RAIC), that adapts a motion trajectory to unexpected forces during loading in a manner that tracks a trajectory closely when loads are low, but avoids excessive loads when significant resistance is met. Our method is evaluated on four terrains using a robotic arm, demonstrating improved excavation performance across multiple metrics, including volume scooped, protective stop rate, and trajectory completion percentage.
Noah Franceschini, Pranay Thangeda, Melkior Ornik, Kris Hauser
ICRA1