no code implementations • 30 Sep 2023 • Snehal Jauhri, Sophie Lueth, Georgia Chalvatzaki
In this work, we introduce an active perception pipeline for mobile manipulators to generate motions that are informative toward manipulation tasks, such as grasping in unknown, cluttered scenes.
no code implementations • 12 Jun 2023 • Snehal Jauhri, Ishikaa Lunawat, Georgia Chalvatzaki
A significant challenge for real-world robotic manipulation is the effective 6DoF grasping of objects in cluttered scenes from any single viewpoint without the need for additional scene exploration.
no code implementations • 27 Sep 2022 • Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Zhiyuan Hu, Jan Peters, Georgia Chalvatzaki
Our proposed approach achieves state-of-the-art performance in simulated high-dimensional and dynamic tasks while avoiding collisions with the environment.
no code implementations • 9 Mar 2022 • Puze Liu, Kuo Zhang, Davide Tateo, Snehal Jauhri, Jan Peters, Georgia Chalvatzaki
Autonomous robots should operate in real-world dynamic environments and collaborate with humans in tight spaces.
no code implementations • 8 Mar 2022 • Snehal Jauhri, Jan Peters, Georgia Chalvatzaki
Finally, we zero-transfer our learned 6D fetching policy with BHyRL to our MM robot TIAGo++.
1 code implementation • 2 Aug 2020 • Snehal Jauhri, Carlos Celemin, Jens Kober
Imitation Learning techniques enable programming the behavior of agents through demonstrations rather than manual engineering.