Keywords: Perception for Grasping and Manipulation, Computer Vision for AutomationĪbstract: We present a robotic grasping system that uses a single external monocular RGB camera as input.
Indirect Object-To-Robot Pose Estimation from an External Monocular RGB Camera Experiments show that these techniques allow an unstructured representation to observe scenes with fewer views and shorter distances while retaining high observation quality and low computational cost. Their performance is evaluated by extending the density-based Surface Edge Explorer (SEE). This paper presents proactive solutions for handling occlusions and considering scene coverage with an unstructured representation. Unstructured representations (e.g., point density) avoid the computational overhead of maintaining and raycasting a structure imposed on the scene but as a result do not proactively predict the success of future measurements. Structured representations (e.g., a voxel grid or surface mesh) typically use raycasting to evaluate the visibility of represented structures but this is often computationally expensive. Approaches often aim to obtain high-quality scene observations while reducing the number of views, travel distance and computational cost.Ĭonsidering occlusions and scene coverage can significantly reduce the number of views and travel distance required to obtain an observation.
Keywords: Computer Vision for Automation, Visual Servoing, Computer Vision for Other Robotic ApplicationsĪbstract: The process of planning views to observe a scene is known as the Next Best View (NBV) problem.
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