Best Viewpoint Tracking for Camera Mounted on Robotic Arm with Dynamic Obstacles

TL;DR

This paper presents a method for dynamically selecting the next best viewpoint for a camera mounted on a robotic arm, considering occlusions, joint constraints, and environment changes to improve 3D scene modeling.

Contribution

It introduces a novel approach for dynamic viewpoint planning that accounts for occlusions and robot constraints in real-time environments.

Findings

Effective in 8 different scenarios with occlusions

Validated on a short 3D video sequence

Demonstrates real-time dynamic viewpoint recovery

Abstract

The problem of finding a next best viewpoint for 3D modeling or scene mapping has been explored in computer vision over the last decade. This paper tackles a similar problem, but with different characteristics. It proposes a method for dynamic next best viewpoint recovery of a target point while avoiding possible occlusions. Since the environment can change, the method has to iteratively find the next best view with a global understanding of the free and occupied parts. We model the problem as a set of possible viewpoints which correspond to the centers of the facets of a virtual tessellated hemisphere covering the scene. Taking into account occlusions, distances between current and future viewpoints, quality of the viewpoint and joint constraints (robot arm joint distances or limits), we evaluate the next best viewpoint. The proposal has been evaluated on 8 different scenarios with different occlusions and a short 3D video sequence to validate its dynamic performance.