Abstract
The article proposes a new path planning method for a multi-robot system for transportation with various loading conditions. For a given system, one needs to distribute given pickup and delivery jobs to the robots and find a path for each robot while minimizing the sum of travel costs. The system has multiple robots with different payloads. Each job has a different required minimum payload, and as a result, job distribution in this situation must take into account the difference in payload capacities of robots. By reflecting job handling restrictions and job accomplishment costs in travel costs, the problem is formulated as a multiple heterogeneous asymmetric Hamiltonian path problem and a primal-dual based heuristic is developed to solve the problem. The heuristic produces a feasible solution in relatively short amount of time and verified by the implementation results.
| Original language | English |
|---|---|
| Journal | International Journal of Advanced Robotic Systems |
| Volume | 16 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2019 Mar 1 |
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Keywords
- functional heterogeneity
- Multi-robot path planning
- pickup and delivery job assignment
- transportation robot system
ASJC Scopus subject areas
- Software
- Computer Science Applications
- Artificial Intelligence
Cite this
Efficient path planning for multiple transportation robots under various loading conditions. / Bae, Jungyun; Chung, Woo Jin.
In: International Journal of Advanced Robotic Systems, Vol. 16, No. 2, 01.03.2019.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Efficient path planning for multiple transportation robots under various loading conditions
AU - Bae, Jungyun
AU - Chung, Woo Jin
PY - 2019/3/1
Y1 - 2019/3/1
N2 - The article proposes a new path planning method for a multi-robot system for transportation with various loading conditions. For a given system, one needs to distribute given pickup and delivery jobs to the robots and find a path for each robot while minimizing the sum of travel costs. The system has multiple robots with different payloads. Each job has a different required minimum payload, and as a result, job distribution in this situation must take into account the difference in payload capacities of robots. By reflecting job handling restrictions and job accomplishment costs in travel costs, the problem is formulated as a multiple heterogeneous asymmetric Hamiltonian path problem and a primal-dual based heuristic is developed to solve the problem. The heuristic produces a feasible solution in relatively short amount of time and verified by the implementation results.
AB - The article proposes a new path planning method for a multi-robot system for transportation with various loading conditions. For a given system, one needs to distribute given pickup and delivery jobs to the robots and find a path for each robot while minimizing the sum of travel costs. The system has multiple robots with different payloads. Each job has a different required minimum payload, and as a result, job distribution in this situation must take into account the difference in payload capacities of robots. By reflecting job handling restrictions and job accomplishment costs in travel costs, the problem is formulated as a multiple heterogeneous asymmetric Hamiltonian path problem and a primal-dual based heuristic is developed to solve the problem. The heuristic produces a feasible solution in relatively short amount of time and verified by the implementation results.
KW - functional heterogeneity
KW - Multi-robot path planning
KW - pickup and delivery job assignment
KW - transportation robot system
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UR - http://www.scopus.com/inward/citedby.url?scp=85063486249&partnerID=8YFLogxK
U2 - 10.1177/1729881419835110
DO - 10.1177/1729881419835110
M3 - Article
VL - 16
JO - International Journal of Advanced Robotic Systems
JF - International Journal of Advanced Robotic Systems
SN - 1729-8806
IS - 2
ER -