This paper presents ADAMANT, a set of software modules that provides grasp planning capabilities to an existing robot planning and control software framework. Our presented work allows a user to adapt a manipulation task to be used under widely different scenarios with minimal user input, thus reducing the operator's cognitive load. The developed tools include (1) plugin-based components that make it easy to extend default capabilities and to use third-party grasp libraries, (2) An object-centric way to define task constraints, (3) A user-friendly Rviz interface to use the grasp planner utilities, and (4) Interactive tools to use perception data to program a task. We tested our framework on a wide variety of robot simulations.
@article{arxiv.2209.06888,
title = {ADAMANT: A Pipeline for Adaptable Manipulation Tasks},
author = {Ana Huamán Quispe and Stephen Hart and Seth Gee and Robert R. Burridge},
journal= {arXiv preprint arXiv:2209.06888},
year = {2022}
}