4 papers
Multi-Resolution Tactile Imitation Learning for Contact-Rich Robotic Manipulation
Rickmer Krohn, Erik Helmut, Niklas Funk +3
Touch sensing is beneficial for solving a wide variety of manipulation tasks. While there exists a wide range of tactile sensors with different properties, exploiting the fusion of…
Global Tensor Motion Planning
An T. Le, Kay Hansel, João Carvalho +5
Batch planning is increasingly necessary to quickly produce diverse and quality motion plans for downstream learning applications, such as distillation and imitation learning. This…
Noise-conditioned Energy-based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation
Anish Abhijit Diwan, Julen Urain, Jens Kober +1
This paper introduces a new imitation learning framework based on energy-based generative models capable of learning complex, physics-dependent, robot motion policies through state…
Grasp Diffusion Network: Learning Grasp Generators from Partial Point Clouds with Diffusion Models in SO(3)xR3
Joao Carvalho, An T. Le, Philipp Jahr +4
Grasping objects successfully from a single-view camera is crucial in many robot manipulation tasks. An approach to solve this problem is to leverage simulation to create large dat…