EDBT 2026 Demo / reviewers in the wild / expert
Jiajun An
dblp:276/8537
· DBLP profile ↗
3ranked-venue papers
0as first author
3since 2021 · last 2025
0000-0002-8624-7076ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3 · 3 since 2021Systems, architecture and hardware · 3 · 3 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | MBE-ARI: A Multimodal Dataset Mapping Bi-Directional Engagement in Animal-Robot Interaction
Ian Noronha, Advait Prasad Jawaji, Juan Camilo Soto, Jiajun An, Upinder Kaur |
ICRA | 4 |
| 2025 | A Variable Stiffness and Transformable Entanglement Soft Robotic GripperabstractFor objects with complex topological and geometrical features, stochastic topological grasping can be executed without the necessity for feedback or precise planning. However, this grasping method has two significant limitations. First, the technique's effectiveness is reduced when interacting with topologically and geometrically simple objects like spheres, cubes, and cylinders, due to the inherent variability in grasping patterns. Additionally, the method's low stiffness restricts its ability to securely handling heavier objects. To address these challenges, this paper proposes an entanglement soft robotic gripper with variable stiffness and two transformed grasping modes (entanglement and clamping modes). The gripper contains three filaments, which can enhance the stiffness through the mechanism of layer jamming. Furthermore, the entanglement mode and the clamping mode, can be transformed by adjusting the working length of the filaments. The grasping performance comparison with and without variable stiffness was carried out, and the results indicated that the implementation of variable stiffness led to a 149 % increase in payload weight. Through experimental validation, we successfully employed the gripper in variable stiffness and transformed modes to grasp items with various shapes and weights. Demonstration of grasping heavier objects and transforming between two grasping modes were also conducted to showcase the adaptability and versatility of the gripper. Tianle Pan, Jianshu Zhou, Boyuan Liang, Jing Shu, Puchen Zhu, Jiajun An |
ICRA | 7 |
| 2023 | Towards Safe Landing of Falling Quadruped Robots Using a 3-DoF Morphable Inertial TailabstractFalling cat problem is well-known where cats show their super aerial reorientation capability and can land safely. For their robotic counterparts, a similar falling quadruped robot problem, has not been fully addressed, although achieving safe landing as the cats has been increasingly investigated. Unlike imposing the burden on landing control, we approach to safe landing of falling quadruped robots by effective flight phase control. Different from existing work like swinging legs and attaching reaction wheels or simple tails, we propose to deploy a 3-DoF morphable inertial tail on a medium-size quadruped robot. In the flight phase, the tail with its maximum length can self-right the body orientation in 3D effectively; before touch-down, the tail length can be retracted to about 1/4 of its maximum for impressing the tail's side-effect on landing. To enable aerial reorientation for safe landing in the quadruped robots, we design a control architecture, which is verified in a high-fidelity physics simulation environment with different initial conditions. Experimental results on a customized flight-phase test platform with comparable inertial properties are provided and show the tail's effectiveness on 3D body reorientation and its fast retractability before touch-down. An initial falling quadruped robot experiment is shown, where the robot Unitree A1 with the 3-DoF tail can land safely subject to non-negligible initial body angles. Yunxi Tang, Jiajun An, Xiangyu Chu, Ching Yan Wong, K. W. Samuel Au |
ICRA | 2 |