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Chanyoung Ahn

Ph.D. student, Purdue University

I teach multi-fingered robot hands to manipulate by touch, and to carry what they learn from simulation to the real world.

I am a Ph.D. student at Purdue University, working in the MARS Lab with Prof. Yu She since Fall 2026. My current project is on dual-arm dexterous manipulation and tool manipulation, built on vision-language-action (VLA) models. Previously, I worked on multimodal perception for dexterous robotic hands at KIST, and built visuotactile reinforcement learning testbeds for deformable object manipulation during my M.Sc. at KAIST.


E-mailCV

News

Publications

  1. Multimodal somatosensory feedback enables physical-object inference and adaptive in-hand manipulation
    Sungwoo Park, Chanyoung Ahn, Jaesung Lee, Donghyun Hwang
    In preparation (journal) 2026
    A robotic hand that synchronizes joint-state proprioception, finger-level interaction-wrench sensing, and fingertip tactile sensing into a single somatosensory state, used to infer physical properties and contact conditions, adapt grasp forces, and condition an in-hand manipulation policy.
  2. HaptiGate: Grasp-Stability Predictor Using Proprioceptive, Kinesthetic, and Tactile Sensing on a Multi-Fingered Robotic Hand
    Jaesung Lee*, Chanyoung Ahn*, Donghyun Hwang
    * Authors contributed equally
    Under review (conference) 2026
    Modality ablations on over 5,220 real-world grasps show that the haptic signal that matters depends on the task, and a prediction-gated recovery strategy raises real-robot grasp success from 64.6% to 77.1%.
  3. Chanyoung Ahn, Jaesung Lee, Sungwoo Park, Donghyun Hwang
    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2026
    Travel Grant: WHPC @ Purdue · IEEE IES-SYPA
    A kinematic-aware, finger-level haptic encoder that complements a pretrained visual pose tracker when the fingers occlude the object, improving sequential tracking and downstream reorientation.
  4. Spotlight
    Chanyoung Ahn, Sungwoo Park, Donghyun Hwang
    CoRL Workshop, Dexterous Manipulation 2025
    A haptic attention estimator that infers object pose from kinesthetic, contact, and proprioceptive signals alone, with average errors of 4.94 mm and 11.6 degrees over 10 seconds of in-hand reorientation.

Projects

  1. Dual-Arm Dexterous Tool Manipulation with Sim-to-Real Learning
    MARS Lab, Purdue University 2026
  2. Dexterous Bimanual Manipulation for Soldering through Haptic Feedback
    Chanyoung Ahn, Sungwoo Park, Jaesung Lee, Donghyun Hwang
    PRIME Lab, KIST 2025

General Engineering

  1. Chanyoung Ahn*, Jaesung Lee*, Donghyun Hwang
    * Authors contributed equally
    ICRA 2025 Arts in Robotics 2025
  2. 6-DoF Grasp Generation for Mobile Manipulation
    Chanyoung Ahn, Taeyoung Lee
    CS492_IIR Final Project @ KAIST 2021

Skills

Simulation Isaac Sim (Lab), MuJoCo, Genesis, PyBullet
RL & ML PyTorch, Stable-Baselines3, RSL-RL
Hardware Denso, Franka, UR5e, KISTAR Hand, F/T sensors, tactile sensors
Programming Python, C++, ROS2

Teaching

Fall 2026 Teaching Assistant, IE 474 Industrial Control Systems, Purdue University

Academic Service

Peer Review T-RO · AIM · IROS · ICRA · ICRA Workshop · CoRL Workshop
Community KRoC Workshop (2025-2026, Korean Robotics Learning Research) · Graspium (KIST paper reading group)