With the increasing number of logistics and automation industries with many potential, the research focuses on increasing efficiency by forming an "autonomous mobile multi-robot system" rather than an autonomous mobile robot (AMR).
Suppliers of autonomous guided vechicles (AGV) and autonomous mobile robots (AMR) inevitably have to compete for costs due to the amount incurred in making robots.
In particular, if multiple robots need to be applied, clueless applications without identifying the facilities and systems to be applied may not match the efficiency that should be prioritized.
Accordingly, autonomous multi-robot parking system research was selected to achieve the ultimate goal of autonomous mobile robots (AMRs) with the minimum number of robots by identifying the system and identifying how many should be applied to be the most efficient.
Based on the above goal, a system will be developed so that parking can be performed autonomously in the parking lot.
Among the various situations, the reasons for selecting the 'parking' situation are as follows.
First, it is to relieve the congestion of parking.
If the parking lot is crowded, there may be situations in which parking is not possible or resources may be wasted to park.
Recently, vehicles capable of parking have been developed and commercialized, but it is not possible to determine where to park in a specific parking lot to be efficient.
In consideration of this point, the autonomous robot will efficiently perform parking in the identified parking lot.
Second, it is for applicability and sustainability.
In some cases, parking towers are built for efficient parking of vehicles. In this case, the entire parking lot is constructed or modified for parking.
This can be judged as a waste of resources from a continuous perspective.
In this situation, parking will be performed by allowing a parking system to be built in an existing parking lot only with the introduction of robots and simple facilities.
The above two reasons for selection and the study look to the near future, not the distant future, in which all vehicles achieve autonomous driving. This research refers to a study to solve the situation in which vehicles capable of autonomous driving, including parking, coexist with vehicles that are not.