Search Results for author: Mark Tjersland

Found 2 papers, 1 papers with code

A Learned Stereo Depth System for Robotic Manipulation in Homes

no code implementations23 Sep 2021 Krishna Shankar, Mark Tjersland, Jeremy Ma, Kevin Stone, Max Bajracharya

We present a passive stereo depth system that produces dense and accurate point clouds optimized for human environments, including dark, textureless, thin, reflective and specular surfaces and objects, at 2560x2048 resolution, with 384 disparities, in 30 ms.

Stereo Matching

SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo

1 code implementation30 Jun 2021 Thomas Kollar, Michael Laskey, Kevin Stone, Brijen Thananjeyan, Mark Tjersland

However, the RGB-D baseline only grasps 35% of the hard (e. g., transparent) objects, while SimNet grasps 95%, suggesting that SimNet can enable robust manipulation of unknown objects, including transparent objects, in unknown environments.

Keypoint Detection Object +5

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