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Yongyi Jia

9 accepted papers

2026

Arm-Aware Guided Dexterous Grasp Generation With Arm-Agnostic Grasp Models

RA-L 2026

Dexterous grasp generation that considers armrelated constraints is crucial in real-world scenarios involving armenvironment collision avoidance, workspace boundary grasps, and consecutive grasping. Existing hand-centric grasp models, which primarily focus on the floating hand's pose, are insufficie

Cited by 0SourcecodeScholar
2026

CoorGrasp: Coordinated Contact Control for Adaptive Dexterous Grasping under Uncertainty

ICRA 2026poster

While recent research has focused heavily on dexterous grasp pose generation, less attention has been devoted to the execution of planned grasps. Under shape and position uncertainty, open-loop execution often yields uncoordinated contacts, causing undesired in-hand object motion and even grasp fail…

Cited by 0codeScholar
2026

Kinematics-Aware Diffusion Policy With Consistent 3D Observation and Action Space for Whole-Arm Robotic Manipulation

RA-L 2026

Full-configuration control of robotic manipulators with awareness of whole-arm kinematics is crucial for many manipulation scenarios involving body collision avoidance or body-object interactions, making it insufficient to consider only the end-effector poses in policy learning. The typical approach

Cited by 1SourceScholar
2025

Flow-Aware Navigation of Magnetic Micro-Robots in Complex Fluids via PINN-Based Prediction

IROS 2025

While magnetic micro-robots have demonstrated significant potential across various applications, including drug delivery and microsurgery, the open issue of precise navigation and control in complex fluid environments is crucial for in vivo implementation. This paper introduces a novel flow-aware na

Cited by 1SourceScholar
2025

Non-Contact Dexterous Micromanipulation With Multiple Optoelectronic Robots

RA-L 2025

Micromanipulation systems leverage automation and robotic technologies to improve the precision, repeatability, and efficiency of various tasks at the microscale. However, current approaches are typically limited to specific objects or tasks, which necessitates the use of custom tools and specialize

Cited by 5SourceScholar
2025

Robotic In-Hand Manipulation for Large-Range Precise Object Movement: The RGMC Champion Solution

RA-L 2025

In-hand manipulation using multiple dexterous fingers is a critical robotic skill that can reduce the reliance on large arm motions, thereby saving space and energy. This letter focuses on in-grasp object movement, which refers to manipulating an object to a desired pose through only finger motions

Cited by 9SourceScholar
2024

Efficient Model Learning and Adaptive Tracking Control of Magnetic Micro-Robots for Non-Contact Manipulation

ICRA 2024poster

Magnetic microrobots can be navigated by an external magnetic field to autonomously move within living organisms with complex and unstructured environments. Potential applications include drug delivery, diagnostics, and therapeutic interventions. Existing techniques commonly impart magnetic properti…

Cited by 3SourceScholar
2023

Contact-Aware Non-Prehensile Manipulation for Object Retrieval in Cluttered Environments

IROS 2023poster

Non-prehensile manipulation methods usually use a simple end effector, e.g., a single rod, to manipulate the object. Compared to the grasping method, such an end effector is compact and flexible, and hence it can perform tasks in a constrained workspace; As a trade-off, it has relatively few degrees…

Cited by 7SourceScholar
2022

Hierarchical Learning and Control for In-Hand Micromanipulation Using Multiple Laser-Driven Micro-Tools

IROS 2022poster

Laser-driven micro-tools are formulated by treating highly-focused laser beams as actuators, to control the tool's motion to contact then manipulate a micro object, which allows it to manipulate opaque micro objects, or large cells without causing photodamage. However, most existing laser-driven too…

Cited by 1SourceScholar