TR2025-094
State Representation Learning for Visual Servo Control
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- "State Representation Learning for Visual Servo Control", European Control Conference (ECC), June 2025. ,
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MERL Contact:
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Research Areas:
Abstract:
We propose a method for visual servo-control of robots using images from an uncalibrated camera that constructs compact state representations of the robot’s con- figuration and uses transition dynamics learned from collected execution traces to compute control velocities to reach a desired goal state identified directly by its image. The key step of the proposed method is the estimation of a homography transform between the image positions of distinct keypoints belonging to the robot in the current image and those in a reference image, which can be done quickly and robustly even when not the same set of keypoints is observed at each time step, making it robust to noise and variations in illumination. The estimated homography is then used to represent the robot configuration as the image coordinates of a minimal number of virtual points moving with the robot. The method was verified experimentally for planar motion of a fully actuated manipulator arm as well as an underactuated mobile robot with a nonholonomic constraint.
Related News & Events
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NEWS MERL contributes to 2025 European Control Conference Date: June 24, 2025 - June 27, 2025
Where: Thessaloniki
MERL Contacts: Stefano Di Cairano; Daniel N. Nikovski; Diego Romeres; Yebin Wang
Research Areas: Control, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization, RoboticsBrief- MERL researchers contributed to both the technical program and workshop organization at the 2025 European Control Conference (ECC), held in Thessaloniki, Greece, from June 24 to 27. ECC is one of the premier conferences in the field of control.
In the main conference, MERL researchers presented four papers covering a range of topics, including: Representation learning, Motion planning for tractor-trailers, Motion planning for mobile manipulators, Learning high-dimensional dynamical systems, Model learning for robotics.
Additionally, MERL co-organized a workshop with the University of Padua titled “Reinforcement Learning for Robotic Control: Recent Developments and Open Challenges.” MERL researcher Diego Romeres also delivered an invited talk titled “Human-Robot Collaborative Assembly” in that workshop.
- MERL researchers contributed to both the technical program and workshop organization at the 2025 European Control Conference (ECC), held in Thessaloniki, Greece, from June 24 to 27. ECC is one of the premier conferences in the field of control.