Imitation learning of robot policies from few demonstrations is crucial in open-ended applications. We propose a new method, Interaction Warping, for learning SE (3) robotic …
D Pavlichenko, S Behnke - 2023 IEEE 19th International …, 2023 - ieeexplore.ieee.org
Many objects such as tools and household items can be used only if grasped in a very specific way-grasped functionally. Often, a direct functional grasp is not possible, though. We …
I Baek, K Shin, H Kim, S Hwang, E Demeester… - Ieee …, 2021 - ieeexplore.ieee.org
An object can be gripped firmly through power grasping, in which the gripper fingers and palm are wrapped around the object. However, it is difficult to power-grasp an object if it is …
M Colombo, L Beretta, AM Zanchettin… - 2024 IEEE 20th …, 2024 - ieeexplore.ieee.org
Object manipulation without relying on complex fixtures remains a largely unresolved issue in industrial robotics, being generally limited to pick-and-place operations of easy to grasp …
In this paper, we propose a novel approach to solve the 3D non-rigid registration problem from RGB images using Convolutional Neural Networks (CNNs). Our objective is to find a …
B Sygo, SC Liu, F Wieczorek, M Koshil… - International Conference …, 2023 - Springer
This paper presents an autonomous robotic system for rearranging books on a shelf. We combine a filtered multi-stage perception approach with a collision-aware manipulation …
In this paper, we propose a novel Deep Reinforcement Learning approach to address the mapless navigation problem, in which the locomotion actions of a humanoid robot are taken …
Efficient and collision-free navigation is an essential requirement for deploying robots in quotidian scenarios. In the robotics community, Reinforcement Learning (RL) approaches …