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Shail V. Jadav

dblp:359/6586 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2024
—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
Robot manipulation · 87% Motion planning and robot control · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation › human-robot interaction
human-robot collaboration
0.812024
Shared Autonomy via Variable Impedance Control and Virtual Potential Fields for Encoding Human Demonstrations · ICRA 2024
Robotics › Robot manipulation › human-robot interaction
shared autonomy
0.812024
Shared Autonomy via Variable Impedance Control and Virtual Potential Fields for Encoding Human Demonstrations · ICRA 2024
Robotics › Motion planning and robot control › robot control › impedance control
variable impedance control
0.212024
Shared Autonomy via Variable Impedance Control and Virtual Potential Fields for Encoding Human Demonstrations · ICRA 2024

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

virtual potential fields · 0.8force control · 0.8energy-tank passivation · 0.8
YearPublicationVenuePosition
2024 Shared Autonomy via Variable Impedance Control and Virtual Potential Fields for Encoding Human Demonstrations
abstract
This article introduces a framework for complex human-robot collaboration tasks, such as the co-manufacturing of furniture. For these tasks, it is essential to encode tasks from human demonstration and reproduce these skills in a compliant and safe manner. Therefore, two key components are addressed in this work: motion generation and shared autonomy. We propose a motion generator based on a time-invariant potential field, capable of encoding wrench profiles, complex and closed-loop trajectories, and additionally incorporates obstacle avoidance. Additionally, the paper addresses shared autonomy (SA) which enables synergetic collaboration between human operators and robots by dynamically allocating authority. Variable impedance control (VIC) and force control are employed, where impedance and wrench are adapted based on the human-robot autonomy factor derived from interaction forces. System passivity is ensured by an energy-tank based task passivation strategy. The framework’s efficacy is validated through simulations and an experimental study employing a Franka Emika Research 3 robot.
Shail V. Jadav, Johannes Heidersberger, Christian Ott 0001, Dongheui Lee
ICRA1