ForgeScan is a library for developing voxelized reconstructions and next-best view selection policies.

Autonomous robotics systems rely on digital reconstructions of environments and objects to make decisions. Whether navigating in an evolving space or interacting with a new object, a system must first observe its surroundings.

ForgeScan breaks this process into three components: data representations, with focus on voxel data structures; next-best view selection algorithms; and distance measurements, from sensors depth cameras.

This project is still in early development and subject to major changes. This is still primarily a research tool in its alpha version. An updated library based on this will be released soon.

Getting Started

Project documentation is available here.

Docker files are provided with a description and documentation of the packages required for developing this code on linux systems[^1].

The following collaboration diagram depicts how the Manager class, containing the reconstruction data representation and implements view selection policies, interacts with simulated depth cameras and overall system.

[^1]: The code will compile on windows if the same packages are installed.