Sep 18, 2021 · In this paper, we explore whether a robot can learn to regrasp a diverse set of objects to achieve various desired grasp poses.
Abstract: In this paper, we explore whether a robot can learn to regrasp a di- verse set of objects to achieve various desired grasp poses.
The key technique includes a neural stable placement predictor and a regrasp graph based solution through leveraging and changing the surrounding environment.
We propose a point-cloud-based system for robots to predict a sequence of pick-and-place operations for transforming an initial object grasp pose to the ...
simPLE learns to pick, regrasp and place objects precisely, given only the object CAD model and no prior experience. We develop three main components: task- ...
Learning to Discern: Imitating Heterogeneous Human Demonstrations with Preference and Representation Learning ... Learning to Regrasp by Learning to Place. Shuo ...
Sep 9, 2024 · SimPLE is a learning-based tool to pick, regrasp and place objects precisely. It doesn't require any prior real-world experience with the objects.
SimPLE, a visuotactile method learned in simulation to precisely ...
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Jun 26, 2024 · SimPLE learns to pick, regrasp, and place objects given the object's computer-aided design model and no prior experience.
Jun 26, 2024 · SimPLE learns to pick, regrasp, and place objects given the object's computer-aided design model and no prior experience.
Abstract—The ability to place objects in an environment is an important skill for a personal robot. An object should not only be placed stably, ...
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