LCPP: Low Computational Processing Pipeline for Delivery Robots

Soofiyan Atar, Simranjeet Singh, Srijan Agrawal, Ravikumar Chaurasia, Shreyas Sule, Sravya Gadamsetty, Aditya Panwar, Amit Kumar, Kavi Arya

2022

Abstract

Perception techniques in novel times have enormously improved in autonomously and accurately predicting the ultimate states of the delivery robots. The precision and accuracy in recent research lead to high computation costs for autonomous locomotion and expensive sensors and server dependency. Low computational algorithms for delivery robots are more viable as compared to pipelines used in autonomous vehicles or prevailing delivery robots. A blend of different autonomy approaches, including semantic segmentation, obstacle detection, obstacle tracking, and high fidelity maps, is presented in our work. Moreover, this method comprises low computational algorithms feasible on embedded devices with algorithms running more efficiently and accurately. Research also analyzes state-of-the-art algorithms via practical applications. Low computational algorithms have a downside of accuracy, which is not as proportional as computation. Finally, the research proposes that this algorithm will be more realizable as compared to Level 5 autonomy for delivery robots.

Paper Citation

in Harvard Style

Atar S., Singh S., Agrawal S., Chaurasia R., Sule S., Gadamsetty S., Panwar A., Kumar A. and Arya K. (2022). LCPP: Low Computational Processing Pipeline for Delivery Robots. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-547-0, pages 130-138. DOI: 10.5220/0010786300003116

in Bibtex Style

@conference{icaart22,
author={Soofiyan Atar and Simranjeet Singh and Srijan Agrawal and Ravikumar Chaurasia and Shreyas Sule and Sravya Gadamsetty and Aditya Panwar and Amit Kumar and Kavi Arya},
title={LCPP: Low Computational Processing Pipeline for Delivery Robots},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2022},
pages={130-138},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010786300003116},
isbn={978-989-758-547-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - LCPP: Low Computational Processing Pipeline for Delivery Robots
SN - 978-989-758-547-0
AU - Atar S.
AU - Singh S.
AU - Agrawal S.
AU - Chaurasia R.
AU - Sule S.
AU - Gadamsetty S.
AU - Panwar A.
AU - Kumar A.
AU - Arya K.
PY - 2022
SP - 130
EP - 138
DO - 10.5220/0010786300003116