1 citations · 2 across the 8 of their papers we have counts for
8 papers
Efficient and Real-Time Motion Planning for Robotics Using Projection-Based Optimization
Xuemin Chi, Hakan Girgin, Tobias Löw +6
Generating motions for robots interacting with objects of various shapes is a complex challenge, further complicated by the robot geometry and multiple desired behaviors. While cur…
Projection-based first-order constrained optimization solver for robotics
Hakan Girgin, Tobias Löw, Teng Xue +1
Robot programming tools ranging from inverse kinematics (IK) to model predictive control (MPC) are most often described as constrained optimization problems. Even though there are…
Demonstration-guided Optimal Control for Long-term Non-prehensile Planar Manipulation
Teng Xue, Hakan Girgin, Teguh Santoso Lembono +1
Long-term non-prehensile planar manipulation is a challenging task for robot planning and feedback control. It is characterized by underactuation, hybrid control, and contact uncer…
Reactive Anticipatory Robot Skills with Memory
Hakan Girgin, Julius Jankowski, Sylvain Calinon
Optimal control in robotics has been increasingly popular in recent years and has been applied in many applications involving complex dynamical systems. Closed-loop optimal control…
Online and Offline Robot Programming via Augmented Reality Workspaces
Yong Joon Thoo, Jérémy Maceiras, Philip Abbet +3
Robot programming methods for industrial robots are time consuming and often require operators to have knowledge in robotics and programming. To reduce costs associated with reprog…
Generative adversarial training of product of policies for robust and adaptive movement primitives
Emmanuel Pignat, Hakan Girgin, Sylvain Calinon
In learning from demonstrations, many generative models of trajectories make simplifying assumptions of independence. Correctness is sacrificed in the name of tractability and spee…
Active Improvement of Control Policies with Bayesian Gaussian Mixture Model
Hakan Girgin, Emmanuel Pignat, Noémie Jaquier +1
Learning from demonstration (LfD) is an intuitive framework allowing non-expert users to easily (re-)program robots. However, the quality and quantity of demonstrations have a grea…
Nullspace Structure in Model Predictive Control
Hakan Girgin, Sylvain Calinon
Robotic tasks can be accomplished by exploiting different forms of redundancies. This work focuses on planning redundancy within Model Predictive Control (MPC) in which several pat…