Demo Data from EDBT 2026 / reviewers in the wild / expert
Jaspreet Singh Dhupia
dblp:158/5557 · also Jaspreet S. Dhupia
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2025
0000-0001-7181-1917ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 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 · 56% Motion planning and robot control · 44% |
Topics — the 5 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot manipulation › object manipulation
multi-object manipulation |
0.8 | 1 | 2024 | Trajectory Planning and Tracking of Multiple Objects on a Soft Robotic Table Using a Hierarchical Search on Time-Varying Potential Fields · IEEE Trans. Robotics 2024 |
Robotics › Robot manipulation › cooperative manipulation
multi-robot manipulation |
0.8 | 1 | 2024 | Trajectory Planning and Tracking of Multiple Objects on a Soft Robotic Table Using a Hierarchical Search on Time-Varying Potential Fields · IEEE Trans. Robotics 2024 |
Robotics › Motion planning and robot control
trajectory planning and tracking |
0.8 | 1 | 2024 | Trajectory Planning and Tracking of Multiple Objects on a Soft Robotic Table Using a Hierarchical Search on Time-Varying Potential Fields · IEEE Trans. Robotics 2024 |
Robotics › Motion planning and robot control
path planning |
0.2 | 1 | 2024 | Trajectory Planning and Tracking of Multiple Objects on a Soft Robotic Table Using a Hierarchical Search on Time-Varying Potential Fields · IEEE Trans. Robotics 2024 |
Robotics › Motion planning and robot control › motion planning › reactive motion generation
potential field method |
0.2 | 1 | 2024 | Trajectory Planning and Tracking of Multiple Objects on a Soft Robotic Table Using a Hierarchical Search on Time-Varying Potential Fields · IEEE Trans. Robotics 2024 |
Methods — techniques the papers use, named apart from their topics
time-varying potential fields · 0.8hierarchical search · 0.8b-spline trajectory generation · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Analyzing food bolus formation during chewing through image segmentation
Shiyi Ren, Bangxiang Chen, Jaspreet Singh Dhupia, Martin Stommel, Weiliang Xu 0001 |
Eng. Appl. Artif. Intell. | 3 |
| 2024 | Trajectory Planning and Tracking of Multiple Objects on a Soft Robotic Table Using a Hierarchical Search on Time-Varying Potential FieldsabstractThis article presents a control strategy to carry out multiobject manipulation on a novelsoft robotictable (SoTa), which is a new form of the planar distributed manipulator. Manipulating multiple delicate objects simultaneously is an attractive feature of SoTa. The challenge here is to coordinate multiple objects in a confined planar space while avoiding interference with each other. The SoTa system adopts a manipulation strategy that includes a planning and a tracking stage for the purpose of sorting objects. The planning stage consists of two phases: 1) discrete path planning to find a path for each object on a grid map with respect to time; 2) trajectory generation to optimize and produce workable trajectories for SoTa. In the discrete path planning phase, a hierarchical searching method based on the time-varying potential field is proposed. Constraints of the SoTa system are modeled and incorporated into the path searching process. In the trajectory generation phase, a piecewise B-spline method is adopted to generate trajectories based on previously found discrete paths. Next, in the tracking stage, the objects are led to their goals along the trajectories ensuring safety and SoTa's capability. The performances of the proposed algorithm were simulated, analyzed, and compared with the conflict-based search method, which is optimal for multiagent path finding. A multiobject manipulation experiment of three objects on a$4\times 4$grid was conducted on the SoTa. The results demonstrated the effectiveness of the proposed control strategy in executing multiobject manipulations for sorting tasks on the SoTa. Zixiao Chen, Zhicong Deng, Jaspreet Singh Dhupia, Martin Stommel, Weiliang Xu 0001 |
IEEE Trans. Robotics | 3 |