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Dan Kruse

dblp:352/0771 · DBLP profile ↗
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1ranked-venue papers
0as 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 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.

Artificial intelligence
1 paper
Robot manipulation · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
dual-arm manipulation
0.912025
In the Wild Ungraspable Object Picking with Bimanual Nonprehensile Manipulation · ICRA 2025
Robotics › Robot manipulation
grasping
0.912025
In the Wild Ungraspable Object Picking with Bimanual Nonprehensile Manipulation · ICRA 2025
Robotics › Robot manipulation
nonprehensile manipulation
0.912025
In the Wild Ungraspable Object Picking with Bimanual Nonprehensile Manipulation · ICRA 2025
Robotics › Robot manipulation › grasping › grasp planning
grasp point selection
0.312025
In the Wild Ungraspable Object Picking with Bimanual Nonprehensile Manipulation · ICRA 2025

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

visual observation · 0.9friction constraints · 0.9force closure · 0.9
YearPublicationVenuePosition
2025 In the Wild Ungraspable Object Picking with Bimanual Nonprehensile Manipulation
abstract
Picking diverse objects in the real world is a fundamental robotics skill. However, many objects in such settings are bulky, heavy, or irregularly shaped, making them ungraspable by conventional end effectors like suction grippers and parallel jaw grippers (PJGs). In this paper, we expand the range of pickable items without hardware modifications using bimanual nonprehensile manipulation. We focus on a grocery shopping scenario, where a bimanual mobile manipulator equipped with a suction gripper and a PJG is tasked with re-trieving ungraspable items from tightly packed grocery shelves. From visual observations, our method first identifies optimal grasp points based on force closure and friction constraints. If the grasp points are occluded, a series of nonprehensile nudging motions are performed to clear the obstruction. A bimanual grasp utilizing contacts on the side of the end effectors is then executed to grasp the target item. In our replica grocery store, we achieved a 90% success rate over 102 trials in uncluttered scenes, and a 67 % success rate over 45 trials in cluttered scenes. We also deployed our system to a real-world grocery store and successfully picked previously unseen items. Our results highlight the potential of bimanual nonprehensile manipulation for in-the-wild robotic picking tasks. A video summarizing this work can be found at youtu. be/gOhOrDuK8jM.
Albert Wu, Dan Kruse
ICRA2