Collaborative Unmanned Aerial Package Pickup and Delivery System

A system using aerial vehicles to autonomously locate and retrieve ground packages of various colors and shapes within a designated area was developed. This system was notable for its use of an innovative rotor configuration that offered a higher degree of control compared to traditional designs. To accurately identify and track the packages, a multi-sensor approach combining vision and Light Detection and Ranging technologies was implemented, integrating data into an extended Kalman filter framework for precise position and velocity estimates. An electro-permanent magnet was employed to securely grab and release the packages, which have a ferrous material. The process of path planning and collision avoidance was conducted in a decentralized manner, leveraging a shared global map among the airborne vehicles. This paper details system technical design, including the integration of various technologies, and shares insights and outcomes derived from its application.

Authors

Institutions

Publication Details

Journal
Unmanned Systems
Published
2024-11-08
DOI
https://doi.org/10.1142/s2301385024500390
Citations
1
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
0.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Collaborative Unmanned Aerial Package Pickup and Delivery System

Thanakorn Khamvilai, Jintasit Pravitra, Takuma Nakamura, Stephen Haviland et al.
1 citations
Unmanned Systems
Advanced Manufacturing and Logistics Optimization
0.35
article

Collaborative Unmanned Aerial Package Pickup and Delivery System

Thanakorn Khamvilai, Jintasit Pravitra, Takuma Nakamura, Stephen Haviland, Dmitry Bershadsky, Eric Johnson
article en
1 citations

Abstract

A system using aerial vehicles to autonomously locate and retrieve ground packages of various colors and shapes within a designated area was developed. This system was notable for its use of an innovative rotor configuration that offered a higher degree of control compared to traditional designs. To accurately identify and track the packages, a multi-sensor approach combining vision and Light Detection and Ranging technologies was implemented, integrating data into an extended Kalman filter framework for precise position and velocity estimates. An electro-permanent magnet was employed to securely grab and release the packages, which have a ferrous material. The process of path planning and collision avoidance was conducted in a decentralized manner, leveraging a shared global map among the airborne vehicles. This paper details system technical design, including the integration of various technologies, and shares insights and outcomes derived from its application.

Unmanned SystemsVol. 14(01)
Texas Tech University (US), Pennsylvania State University (US), Navamindradhiraj University (TH), Optima Neuroscience (United States) (US)
Openalex Percentile: Top 34%
Advanced Manufacturing and Logistics Optimization
0.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.