Authors:
Soofiyan Atar
1
;
Simranjeet Singh
1
;
Srijan Agrawal
2
;
Ravikumar Chaurasia
3
;
Shreyas Sule
4
;
Sravya Gadamsetty
5
;
Aditya Panwar
1
;
Amit Kumar
1
and
Kavi Arya
1
Affiliations:
1
Indian Institute of Technology Bombay, Mumbai, India
;
2
Shri G. S. Institute of Technology and Science, Indore, India
;
3
University of Mumbai, Mumbai, India
;
4
D Y Patil’s Ramrao Adik Institute of Technology, Mumbai, India
;
5
Indian Institute of Technology Bhubaneswar, Bhubaneswar, India
Keyword(s):
Delivery Robot, Semantic Segmentation, Object Detection.
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 m
ore realizable as compared to Level 5 autonomy for delivery robots.
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