View Planning

View planning, the process of strategically selecting viewpoints for optimal data acquisition, is a crucial area of robotics and computer vision research aimed at maximizing information gain and efficiency in tasks like 3D reconstruction, object mapping, and autonomous navigation. Current research focuses on developing algorithms that leverage various techniques, including neural networks (e.g., for predicting required views or evaluating view quality), graph-based methods (for efficient search of optimal view sequences), and integration of geometric priors (from 3D models or shape completion) to improve view selection. These advancements have significant implications for applications ranging from agricultural robotics and building inspection to autonomous exploration and motion capture, enabling more efficient and robust data collection in challenging environments.