45 citations · 48 across the 7 of their papers we have counts for
7 papers
PokeFlex: A Real-World Dataset of Volumetric Deformable Objects for Robotics
Jan Obrist, Miguel Zamora, Hehui Zheng +5
Data-driven methods have shown great potential in solving challenging manipulation tasks; however, their application in the domain of deformable objects has been constrained, in pa…
PokeFlex: Towards a Real-World Dataset of Deformable Objects for Robotic Manipulation
Jan Obrist, Miguel Zamora, Hehui Zheng +3
Advancing robotic manipulation of deformable objects can enable automation of repetitive tasks across multiple industries, from food processing to textiles and healthcare. Yet robo…
Embracing Safe Contacts with Contact-aware Planning and Control
Zhaoting Li, Miguel Zamora, Hehui Zheng +1
Unlike human beings that can employ the entire surface of their limbs as a means to establish contact with their environment, robots are typically programmed to interact with their…
TRTM: Template-based Reconstruction and Target-oriented Manipulation of Crumpled Cloths
Wenbo Wang, Gen Li, Miguel Zamora +1
Precise reconstruction and manipulation of the crumpled cloths is challenging due to the high dimensionality of cloth models, as well as the limited observation at self-occluded re…
RL + Model-based Control: Using On-demand Optimal Control to Learn Versatile Legged Locomotion
Dongho Kang, Jin Cheng, Miguel Zamora +2
This paper presents a control framework that combines model-based optimal control and reinforcement learning (RL) to achieve versatile and robust legged locomotion. Our approach en…
Gradient-Based Trajectory Optimization With Learned Dynamics
Bhavya Sukhija, Nathanael Köhler, Miguel Zamora +4
Trajectory optimization methods have achieved an exceptional level of performance on real-world robots in recent years. These methods heavily rely on accurate analytical models of…
Learning Solution Manifolds for Control Problems via Energy Minimization
Miguel Zamora, Roi Poranne, Stelian Coros
A variety of control tasks such as inverse kinematics (IK), trajectory optimization (TO), and model predictive control (MPC) are commonly formulated as energy minimization problems…