15 citations · 56 across the 14 of their papers we have counts for
5 papers · 1 filter
Sim-to-Real Transfer of Compliant Bipedal Locomotion on Torque Sensor-Less Gear-Driven Humanoid
Shimpei Masuda, Kuniyuki Takahashi
Sim-to-real is a mainstream method to cope with the large number of trials needed by typical deep reinforcement learning methods. However, transferring a policy trained in simulati…
Cluttered Food Grasping with Adaptive Fingers and Synthetic-Data Trained Object Detection
Avinash Ummadisingu, Kuniyuki Takahashi, Naoki Fukaya
The food packaging industry handles an immense variety of food products with wide-ranging shapes and sizes, even within one kind of food. Menus are also diverse and change frequent…
Target-mass Grasping of Entangled Food using Pre-grasping & Post-grasping
Kuniyuki Takahashi, Naoki Fukaya, Avinash Ummadisingu
Food packing industries typically use seasonal ingredients with immense variety that factory workers manually pack. For small pieces of food picked by volume or weight that tend to…
Collision-free Path Planning in the Latent Space through cGANs
Tomoki Ando, Hiroki Mori, Ryota Torishima +4
We show a new method for collision-free path planning by cGANs by mapping its latent space to only the collision-free areas of the robot joint space. Our method simply provides thi…
Learning-based Collision-free Planning on Arbitrary Optimization Criteria in the Latent Space through cGANs
Tomoki Ando, Hiroto Iino, Hiroki Mori +5
We propose a new method for collision-free planning using Conditional Generative Adversarial Networks (cGANs) to transform between the robot's joint space and a latent space that c…