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João Jantalia

dblp:304/4262 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 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.

Human-computer interaction and pervasive computing
1 paper
Human-robot interaction · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction
physical human-robot interaction
0.512021
CSM: Contact Sensitivity Maps for Benchmarking Robot Collision Handling Systems · ICRA 2021
Embedded and real-time systems
collision detection
0.112021
CSM: Contact Sensitivity Maps for Benchmarking Robot Collision Handling Systems · ICRA 2021

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

experimental comparison · 1.0benchmarking procedure · 1.0
YearPublicationVenuePosition
2021 CSM: Contact Sensitivity Maps for Benchmarking Robot Collision Handling Systems
abstract
In physical human-robot interaction (pHRI), robots need to detect and react to intended and unintended contacts in a safe manner. Proprioceptive sensing capabilities and collision detection and identification techniques differ among commercially available robots, which means that also their sensitivity to detect dynamic collisions with the environment or the human co-worker differ. Up to now, there exists no standardized procedure for assessing the contact sensitivity of a robotic system. In this paper, we propose the concept of contact sensitivity maps (CSM), a relationship between the robot's dynamic impact properties and the reliability of its collision handling. The CSM allows the robot user to determine for which robot workspace areas and dynamic collision parameters (mass, velocity) reliable contact detection and reaction can be expected. We propose a standardized benchmarking procedure and test setup for deriving CSMs. Finally, we analyze and compare the experimental results of the Universal Robots UR10e, UR5e, and Franka Emika Panda, where we observe significant differences in contact sensitivity.
Robin Jeanne Kirschner, João Jantalia, Nico Mansfeld, Saeed Abdolshah, Sami Haddadin
ICRA2