Abstract
This paper will investigate the feasibility and design considerations of autonomous luggage and cargo handling equipment to streamline operations, reduce manpower, and to increase safety in the vicinity of the aircraft during ground operations. Potential designs will be investigated including power sources, decision logic, and how these systems may be incorporated into the existing infrastructure of currently operating airports. Human factors are considered and discussed including how to implement operations at airports and to prevent conflict between the workers conducting ground operations and the robotic units. Lastly, how these units will benefit the flying public and the airlines themselves by adopting and implementing these units to streamline cargo and luggage operations are considered.
Introduction
Luggage and cargo operations for transport category commercial airlines are labor intensive and time critical. These operations, for the most part, resemble organized chaos to get the passenger’s luggage loaded on the correct aircraft. Airports design gates to maximize aircraft parking while maintaining minimal separation between aircraft. This presents a problem for the already congested area around the aircraft as cargo containers and luggage trailers are usually staged at the gate before arrival to speed up the process.
This requires extra equipment that must remain idle when not in use, to further compound the problem, the luggage trailers require a small tractor unit to shuttle them between loading and unloading operations. Their standard size of 5 feet wide by 10 feet long limits their maneuverability (Aero Specialties, n.d.). Configurations must be limited to a small number of trailers in a unit because of proximity to the aircraft and safety considerations which vary by the airline but are usually a maximum length of 4 trailers per tug.
The same is true for cargo operations, although they have become standardized with containerized systems to speed loading increase security, with cargo and luggage operations occurring at the same time, vehicle congestion around the aircraft is a common problem (IATA, n.d.). This congestion is compounded by the maintenance operations that must also occur during the limited ground time between flights. With shrinking profit margins and decreased ground time, the chance for human error causing damage to the aircraft increases. Particularly with baggage and cargo operations as they are usually comprised of unskilled labor. Damage to aircraft during ground operations is entirely preventable if all safety protocols are followed, but human nature being what it is, not all procedures usually are, resulting in damage that can interrupt flight operations and cause delays.
This paper will investigate the possibility of using independently powered robotic luggage and cargo trailers to decrease congestion around the aircraft, reduce unskilled manpower, reduce the use of powered equipment such as tugs, and increase the safety of ground operations by limiting the amount of equipment that is in proximity to the aircraft. The design and operation of the units will be made to easily integrate into airport infrastructure because of the standardization that has occurred within the industry due to international agreements (IATA, 2017).
There will be problems to overcome, although airports are a controlled environment per se, not all people that work there follow the established rules, therefore the logic that controls the units will have to be sufficiently advanced to deal with any issue that it encounters. Furthermore, this will not entirely eliminate the use of human labor during the luggage and cargo handling procedures, but it will contribute to safer and more efficient operations. The speeding up of ground services for the aircraft will increase the frequency that a gate can be used, reduce the number of gate changes due to loading delays, and allow the operator to adhere to its schedule.
The use of the proposed robotic system will reduce the amount of equipment needed to perform these operations, due to their ability to operate independently, they will not have to be loaded and staged before aircraft arrival, and when ground operations are complete, the units can be utilized to unload another aircraft immediately after finishing an assignment. This will reduce the amount of equipment clutter around a parked aircraft and also eliminate ancillary equipment needed for the unpowered trailers. The utilization of robotic luggage and cargo trailers will also enhance airline operations by improving efficiency, reducing costs, and increasing safety around the aircraft through the reduction of human error.
Background
Aircraft ground operations are laborious, chaotic, and time critical in the airline industry. Passenger and cargo must be loaded quickly during the short window of ground time allotted for refueling and maintenance. Due to the proximity of the aircraft to ground equipment, that chance that it will be damaged increases. This is where the human factors come into the equation as aircraft baggage handlers have some of the highest rates of physical injuries and lowest job satisfaction among all of the employee classifications in the industry (Sıdıka Bulduk, 2017). There is a trend in any industry where the unskilled laborers are being replaced with robotic systems, the same thing occurred in certain cottage industries when the first industrial revolution took place (Andrew Berg, 2018).
Labor is the largest expense for an airline, most of it being unskilled and highly unionized, this forces the airline to subsidize the wages of the unskilled at the expense of skilled labor such as the certificated aircraft mechanics (Doganis, 2019). They are administrated by the Railway Labor Act and the National Labor Relations Board, strikes are rare, but disruptions can occur, particularly if the organized workers see the skilled labor group gain more than the unskilled in negotiations. This causes problems for paying passengers and delays for the operations. With the integration of flight schedules and code sharing agreements, a cascade event such as a work slowdown at one airline can affect the others causing congestion and disruption to the global airline system (Gerald N. Cook, 2017). Removing the impact of work disruptions to the operations will ensure that the airline can maintain schedule and be profitable.
Airline operations are a logistic system at the mercy of a myriad of factors such as weather, fuel, and labor. The weather cannot be controlled, fuel pricing is at the whim of the market and political instability in oil rich areas, labor is one of the few factors in the equation that airlines have direct control over. To achieve this, the use of robotic systems must be implemented to control costs and increase the reliability of the operations. The trend to automate systems in air travel that interface with the customer is already being implemented at major airports from ticket kiosks to luggage scanning (Nicole Hättenschwiler, 2018). The next step in the process is to reduce the manpower and equipment needed to transport the luggage and cargo to and from the airplane. With a robotic system, the following can be achieved; reduction in manpower, clearing of the equipment clutter around the aircraft, streamlining of the loading procedures, and elimination of idle equipment. The problem is not insurmountable but does have some obstacles, firstly the proposed units will have to be implemented into already established airport infrastructure. Secondly, units will have to be designed to accommodate the dynamic environment of the airport and operate closely with both human and aircraft traffic. Lastly, the units will have to be as close to the standardized and accepted design of airport ground servicing equipment to ensure its acceptance by the airline operators. By making the equipment familiar in size and shape, it will also decrease the training time required to use it.
The dynamic nature of ground traffic at an airport will require a sophisticated algorithm where the primary mission will be object avoidance (Yadav, 2017). Vehicle traffic on the air operations area (AOA) is strictly controlled, aircraft have the right of way, therefore geofencing may be an appropriate method to restrict movement and to also have established paths for the units to travel to prevent inadvertent contact with human manned vehicles and aircraft. Visual sensors will also be required such as light detection and ranging (LiDAR) , the unmanned ground vehicles (UGV) mounted with LiDAR and then connected to a neural network to coordinate path planning with be advantageous as the units would act cooperatively to deliver the luggage to and from the aircraft (Wei Song, 2018). By networking the units together, it could assist with path planning and utilization based on demand and aircraft schedules.
The infrastructure of the airport will also have to be modified, from charging stations to markings at the gate to direct the unit where to stage and to deliver its cargo (Marie-Anne Bauda, 2017). A robotic inspection unit named Air-Cobot is already using a combination of LiDAR and visual information to accomplish an inspection of aircraft for maintenance issues, this technology could be used to position the cargo units for unloading and object avoidance (Javier Ramirez Leiva, 2017). The tight confines of the aircraft gate area are also a factor in the design and maneuverability of the units. To accomplish this direct drive electrical motors will be utilized. There will be no conventional steering mechanism, this eliminates parts which could be a foreign object debris (FOD) hazard to aircraft if anything breaks off and it simplifies maintenance. Instead, there will be mecanum wheels on all four axles, this will greatly increase its ability for obstacle avoidance to operate in close proximity to the aircraft as they can change the direction of the unit based on the rotation of the wheel (Yiqun Liu, 2017). Obstacle avoidance, maneuverability, ability to integrate into existing infrastructure, and increasing the safety of the aircraft are all goals of this proposed project.
Recommendations
Because of the standardization of airport equipment, particularly with cargo and luggage handling, it is required to design a unit that has the same footprint as those currently in use. This serves two functions, it allows the equipment to be integrated into airport operations with minimal modifications to the existing infrastructure and encourages acceptance by the ground workers who will be in proximity to the units (Timo Gnambs, 2019). It has been proven that any segment of an industry that relies heavily on unskilled labor and is unionized usually have problems integrating robotic systems into the workforce due to fear of job losses (Zhang, 2019). To prevent resistance from the human workforce replacement of the workers shall be done on the basis of attrition.
The equipment must be ruggedized, to accomplish this only proven stable technologies will be used for the units and control systems, for example, although lithium batteries offer some of the highest power density of all they are somewhat fragile and can be damaged easily (Kai Lui, 2018). Therefore, deep cycle lead acid batteries that can much better handle charging anomalies and the environment of the AOA will be used. This has the added benefit of keeping maintenance costs predictable as the battery technology is not dependent on the availability of rare earths and the ground equipment maintenance personnel will already be familiar with them.
The units will have four electric motors, one on each wheel, to minimize complexity and as a safety factor. If any one motor fails during normal operation it will be able to enter a limp mode and depending on which phase of the operation it experienced trouble it, can then head to the designated maintenance area. The four drive motors will also give it unprecedented maneuverability when coupled with mecanum wheels, this configuration will allow the unit to go straight, sideways and to rotate within its own footprint to position itself at the required loading/unloading point (Yiqun Liu, 2017).
Positioning the units near the aircraft will be one of the most critical tasks the units will have to accomplish, to assist in this there will need to be markings around the aircraft that the logic of the unit will be able to identify coupled with its LiDAR scans of the aircraft (Javier Ramirez Leiva, 2017). The ground markings would have to be reflective so that the vision based sensors would be able to pick them up under all conditions day or night and to position them correctly (Sergey Astanin, 2017). The ramp workers, which are already required to wear reflective clothing, will be detectable as well, this will increase safety and prevent the units from causing injury (Rafael Mosberger, 2014). This visual identification of human workers through the use of mandatory safety vests is more cost effective than using separate equipment that identifies the humans from the robots in a typical industrial setting such as a warehouse where they may interact, systems like this are in use by Amazon when workers must enter the robotic area (Jana Jost, 2018). On the AOA there will be no segregation of the robotic and human workforce.
Since the purpose of the robotic luggage units is to reduce ground clutter and to increase efficiency in operations, they will be in continuous use implementing a just in time strategy. Luggage and cargo will be held at the staging area until picked up and transported to the aircraft for direct loading. Scheduling of the units will be handled by a neural net; this will allow a degree of adaptability and to efficiently utilize the equipment (Nancy Arana-Daniel, 2018). The order of loading will be determined to ensure the center of gravity (CG) is within aircraft operating limits. The use of radio frequency identification tags (RFID) on both the individual bags and cargo containers will ensure that no luggage is loaded on the cart that does not belong (T. Bouhouche, 2017).
Transiting to and from the AOA will have to have strict rules established, perhaps even routes only traveled by the units themselves. This will reduce the chance that there is an inadvertent encounter with an aircraft moving to the gate area. Object avoidance will be the primary function of the units with its secondary as transporting luggage, the use of vision based sensors coupled with the LiDAR and geofencing will accomplish this control of the unit with scheduling accomplished by the neural net (Andrew J. Barry, 2017). Even though AOA speeds are typically limited to 15 miles per hour, the units will most likely be traveling at this rate to ensure efficiency, this will result in abrupt movements and changes in direction. The navigation and sensing logic must be of sufficient speed to adapt to the dynamic environment of the AOA with minimal input from the supervisory neural net.
Communication between the units and the supervisory program will be accomplished through the wireless networks already established at the airports, the units may incorporate cellular modems as a backup. This will allow remote monitoring by the operator and the ability to intervene and take manual control in case of malfunctions. To ensure safety, control could be turned over to a human operator when the unit reaches a predetermined spot at the gate and final positioning accomplished by a human operator via remote control with a handheld unit. Paired with a kinetostatic safety field, this will allow the integration the robotic and human workforces to collaborate at the gate while preventing injuries from unexpected movements of the units in proximity of the aircraft (Matteo Parigi Polverini, 2017).
The drivetrain will be key to the maneuverability of the units. Instead of a traditional steering mechanism with turning wheels or a skid steer setup, it will be equipped with mecanum wheels. As mentioned previously, these wheels are unique in their construction as they allow a vehicle to rotate 360 degrees within its own footprint (Yiqun Liu, 2017). By varying the speed and rotational direction of the wheel, the unit can be steered at any angle to get to the pickup or drop off points (Yiqun Liu, 2017). This will reduce the amount of equipment needed around the aircraft and with proper utilization of just in time principals for luggage and cargo delivery, increase the efficiency of operations. Decluttering the gate area increases the margin of safety to prevent aircraft damage from moving equipment that is traditionally towed or equipment that has been improperly stored with the brakes not set. Open spaces around the aircraft also contribute to safer maintenance practices as the mechanics’ exposure to work related injuries is decreased such as trip hazards.
The use of “just in time” delivery principals for aircraft luggage and cargo operations will reduce the amount of time the units are idle and increase their utilization. Although individual passenger check in time cannot be mandated, it is suggested that they arrive in sufficient time to clear security and to allow bag inspection to take place, there are now automated systems that can handle baggage screening to speed up the process with more accuracy than human counterparts (Nicole Hättenschwiler, 2018). Attaching an RFID tag and automating most of the luggage and cargo handling processes has the effect of reducing the amount of human labor required and increase security of the passenger’s belongings as the interaction with human workers is decreased. The less luggage is handled by human labor, the more efficiently it can be routed to the appropriate gate and aircraft.
Using a supervisory control system to schedule the units for pick up and drop off while allowing the units themselves to choose the shortest path would be the most efficient method of operation, although linked to a neural net, once given instructions, the unit will operate independently (Nancy Arana-Daniel, 2018). Established pathways and routes for safe operation may have to be implemented, limiting human interaction in these areas and will reduce the chances for injury and prevent unpredictable behavior. Airports that are currently in operation may have to make modifications to the traffic patterns around the gates to accomplish this. Facilities not constructed yet could have the accommodations incorporated into the design thus encouraging the use of the units. Once the units reach the assigned gate, the human workers could become the supervisory control element. This collaboration between the humans and the robots will promote acceptance among the workforce and give them control over the final stage of the loading procedure (Selma Musić, 2017). It will also act as an additional layer of safety to prevent injury to the ground workers. The control unit used by the ground workers must be simple and rugged with as few commands as possible to prevent inadvertent movements and require a minimum of training.
The charging of the units will be accomplished automatically, designated charging stations will have to be incorporated to the infrastructure, once the battery state reaches a predetermined level the control agent will direct it to recharge. During routing, the units could be linked together to form a train, sharing the energy, then leaving at the appropriate destination. By combining during locomotion, energy is conserved and could be transferred to units that are approaching the point of requiring batteries needing a charge. An alternate method could be the inclusion of a small diesel powered generator but this will require the replenishment of the fuel which would negate the costs savings of being electrically powered.
Human factors will have to be considered, robots will behave in a predictable manner based on their programming and control mechanisms, people are the complete opposite. Using human factors principals in the design and use of the system in an airline environment will increase safety and productivity while decreasing costs (Przemyslaw A. Lasota, 2015). By setting strict operating rules when in the vicinity of human workers such as maximum speed and rate of maneuvering, the chances of injury will be decreased. If any of the safety systems are disabled by the human operators, which has been known to happen in other industries resulting in injury or death, the units will immediately head for repair to correct the situation. Adding a set of failsafe instructions to the units will provide an additional layer of safety to protect the aircraft and ground workers in case of malfunctions with the machine. Robotic technology has reached the beginning of maturation, safety around an integrated workforce has become the chief concern among industries that use them. Concentrating on how they interact with a dynamic environment is the primary concern of designers and engineers, no longer just focused on the completion of a specific task but also operating in a changing environment with many variables (B. N. Sharma, 2017).
Conclusions
The use of robotic systems is expanding, once relegated to fixed positions in industry completing repetitive tasks such as spot welding in automotive manufacturing, but now the logic and control software has advanced enough to operate in a variable environment such as an airport gate area. Aircraft baggage and cargo handling operations can benefit from the addition of autonomous just in time delivery to remove equipment clutter from the gate, increase the safety of the aircraft, and reduce the amount of unskilled labor required for these operations which have the added benefit of lowering costs. For this to happen the units must be a standard size to integrate with existing equipment and infrastructure, be durable enough to operate outside in the harsh environment of the airport and to tolerate rough handling by the ramp operations employees.
The integration of robots into the operation will at
first be resisted by the unionized workforce fearing job losses, as attrition
reduces their numbers, the capital investment and maintenance costs will be
offset by more efficient luggage and cargo operations. Passengers will be drawn
to operations that can reduce their wait time at the luggage carousel and cargo
operations will be more secure as the amount of handling will be reduced. Airport
operations will be streamlined even more with the complete automation of
luggage transportation and costs will be reduced due to manpower and equipment
reductions. Eventually, aircraft will be piloted by artificial intelligence,
but due to public perception, it is theorized that this will be the last sector
of mass transportation to succumb to automation, unskilled labor will be the
first to be replaced.
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Patrick Carroll 