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Start date: Any time
Assignment duration: 6 months
Context
Autonomous vehicles (AVs) bring flexibility to warehousing, airport baggage handling, and parcel sorting. However, to combine this flexibility with high throughput in tight spaces, fine-grained coordination between the AVs is necessary. To that end, Vanderlande has developed a Fleet Management System (FMS). This FMS is responsible for controlling AVs in such a way that the system reaches the highest throughput feasible without collisions or deadlocks.
Problem description
One of our algorithms is a multi-agent path planner based on Cooperative A*; it plans paths of all the AVs fully in space and time for active jobs in real-time. This fully prevents deadlocks and offers possibilities for high optimization. However, due to the algorithm design, this can only be done single-threaded. As this significantly limits the scalability or resulting throughput, we want to extend the algorithm’s capabilities through parallelization.
Tasks / responsibilities
Department
Vanderlande Industries delivers material handling systems to control product flows in warehousing, sorting centers for package delivery, and baggage handling systems on airports.
Within Vanderlande, FLEET is responsible for developing solutions based on autonomous vehicle technology. These activities are carried out in close cooperation with other companies within Toyota Industries.
Your profile
Vanderlande is the global market leader for value-added logistic process automation at airports, and in the parcel market. Vanderlande’s baggage handling systems move 4.2 billion pieces of luggage around the world per year. Its systems are active in 600 airports including 14 of the world’s top 20.
Resources:
Change language to: English
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