6 papers
Simultaneous Pick and Place Detection by Combining SE(3) Diffusion Models with Differential Kinematics
Tianyi Ko, Takuya Ikeda, Balazs Opra +1
Grasp detection methods typically target the detection of a set of free-floating hand poses that can grasp the object. However, not all of the detected grasp poses are executable d…
GTR: Gaussian Splatting Tracking and Reconstruction of Unknown Objects Based on Appearance and Geometric Complexity
Takuya Ikeda, Sergey Zakharov, Muhammad Zubair Irshad +8
We present a novel method for 6-DoF object tracking and high-quality 3D reconstruction from monocular RGBD video. Existing methods, while achieving impressive results, often strugg…
ZeroGrasp: Zero-Shot Shape Reconstruction Enabled Robotic Grasping
Shun Iwase, Zubair Irshad, Katherine Liu +8
Robotic grasping is a cornerstone capability of embodied systems. Many methods directly output grasps from partial information without modeling the geometry of the scene, leading t…
A Planar-Symmetric SO(3) Representation for Learning Grasp Detection
Tianyi Ko, Takuya Ikeda, Hiroya Sato +1
Planar-symmetric hands, such as parallel grippers, are widely adopted in both research and industrial fields. Their symmetry, however, introduces ambiguity and discontinuity in the…
Gravity-aware Grasp Generation with Implicit Grasp Mode Selection for Underactuated Hands
Tianyi Ko, Takuya Ikeda, Thomas Stewart +2
Learning-based grasp detectors typically assume a precision grasp, where each finger only has one contact point, and estimate the grasp probability. In this work, we propose a data…
ViFu: Multiple 360 Objects Reconstruction with Clean Background via Visible Part Fusion
Tianhan Xu, Takuya Ikeda, Koichi Nishiwaki
In this paper, we propose a method to segment and recover a static, clean background and multiple 360 objects from observations of scenes at different timestamps. Recent wo…