Kernkonzepte
FlowBot++ is a deep 3D vision-based robotic system that predicts dense per-point motion (Articulation Flow) and dense per-point articulation parameters (Articulation Projection) to enable generalized manipulation of articulated objects.
Zusammenfassung
The paper presents FlowBot++, a deep 3D vision-based robotic system that can manipulate a wide range of articulated objects, including novel objects not seen during training.
Key highlights:
- FlowBot++ introduces a novel per-point representation called Articulation Projection, which captures the articulation parameters of the object in addition to the per-point motion (Articulation Flow) predicted in prior work.
- By jointly predicting Articulation Flow and Articulation Projection, FlowBot++ can infer the full articulation parameters of the object and plan a smooth, multi-step trajectory to actuate the object, outperforming prior methods that only predict instantaneous motion.
- Experiments in simulation on the PartNet-Mobility dataset and real-world trials on a Sawyer robot demonstrate the generalization capabilities of FlowBot++ to manipulate a diverse set of articulated objects, including unseen categories.
- FlowBot++ is able to produce smoother and more consistent motions compared to prior work, while also being more efficient by replanning less frequently.
Statistiken
"Understanding and manipulating articulated objects, such as doors and drawers, is crucial for robots operating in human environments."
"Previous approaches for articulated object manipulation rely on either modular methods which are brittle or end-to-end methods, which lack generalizability."
"FlowBot++ introduces a novel per-point representation of the articulated motion and articulation parameters that are combined to produce a more accurate estimate than either method on their own."
"Simulated experiments on the PartNet-Mobility dataset validate the performance of our system in articulating a wide range of objects, while real-world experiments on real objects' point clouds and a Sawyer robot demonstrate the generalizability and feasibility of our system in real-world scenarios."
Zitate
"FlowBot++ leverages these predictions to produce a smooth sequence of actions that articulate the desired part on the object."
"By estimating per-point predictions, we leverage the advantages of prior work [6] that has shown that per-point predictions enable enhanced generalization to different object geometries and kinematics."
"Experiments demonstrate that this approach shows superior generalization to unseen articulated objects."