El Cerrito del Norte station

Transcription

Hello, and welcome to the 2013 Aeronautics Academy at NASA Ames Research Center. We are Team RAPTOR, a demonstration and proof-of-concept study for Rotorcraft Applications for Public Transportation. Our principal investigators are Sumeet Singh and Dr. William Warmbrodt. This summer, we purchased and tested commercial-off-the-shelf remote control ground vehicles and quadcopters to demonstrate a future urban transportation system in a simulated urban environment. Our goal is to produce simulation, demonstration techniques, design concept studies, and system solutions for future augmentation into existing public transportation systems, specifically in the Bay Area. The team spent the first of many meetings scoping the project by defining requirements and deliverables as well as testing methods to verify and validate the mission objectives. The team met with folks from Flightline and Facilities Management to determine which locations on center would be suitable to conduct rover and quadcopter operations. At that point, we were able to begin the experimental portion of our study. We began by constructing our quadcopter vehicles after they arrived in the mail. Alan, Matt, Karly, Robyn and Andrew C. met at Building 243 to construct the quadcopters on a Friday afternoon. After all 4 quadcopters were assembled, we finally turned them on using remote control to hear the engines first time roar. Oooh! That was cool! Next, we began using Mission Planner and QGroundControl to prepare the vehicle for autonomous flight. Alan and Andrew T.calibrated the on-board accelerometers by holding the quadcopter in various positions to tell the on-board accelerometers which direction was up or down. Aliyeh, Andrew C., Christina, and Alan used QGroundControl to make first communication with the quadcopters. All right! Our first programmed flight. Good job! Way to go! However, our first flights were not as smooth as anticipated. For unknown reasons, the quadcopters would repeatedly surge unexpectedly to high altitudes, causing the quadcopter to crash when flown indoors. Achieving stable flight was also found to be very difficult. We went back to square one and determined that the main problems lied within the altimeter and battery. The altimeter had hidden calibration issues causing the vehicle to climb to high altitudes without commands. The team also found a loose battery connection, causing the auto-pilot to reboot in mid flight. This explained the unexpected instances where the engine would shut-off. And that s when the battery cut out. There you go! Battery cut out. Could that be a dead battery? No, it's not a dead battery. It's a loose wire. The team reconvened and re-attached the batteries onto the vehicle using stronger adhesive and fixtures. The team went back to MissionPlanner to determine where the altimeter calibration was incorrect. Looking through the algorithms, the incorrect altitude calibrations were found and fixed accordingly. With these new solutions, the quadcopter was capable of achieving stable flight and performing individual operations autonomously through ground-station commands. Here, Sumeet and Andrew C. command the quadcopter to perform a hovering maneuver using the groundstation laptop within the laboratory. Once the quadcopters proved that they could fly autonomously using ground-station commands, the team began creating waypoint missions using MissionPlanner. For safety precautions, waypoint missions were uploaded to the rover vehicles first, to prevent catastrophic failures such as drops and/or out-of-control spins as discussed earlier. The team conducted their waypoint missions in a parking-lot, successfully demonstrating that a vehicle can autonomously navigate point-to-point using GPS. Three waypoint missions were selected in order of importance. A minimum success mission involves a single quadcopter autonomously flying from station 1 to station 2. A project success encompasses multiple quadcopters flying between separate stations in sequence. Finally, a stretch goal mission involves a corridor operation, where 2 quadcopters from separate stations rendezvous in mid air and fly and land into a shared destination. In this video, the stretch goal mission is performed. Seen above the horizon, two quadcopters take off from separate locations. They rendezvous at a determined location in mid-air, before flying in formation to a shared destination. There, they land in order depending on a set flight priority. After each test, a 3D representation of the flight is created using the flight-log data from Mission Planner, which can be seen in the top left corner. This is then compared with the pre-determined path, which allows the team to characterize the vehicle performance and its ability to execute its mission profile. The second major portion of the study involves the theoretical full-scale applications of our project. One of RAPTOR s major goals is to allow easy implementation of VTOL passenger aircraft into today s existing transportation systems. Eight major areas within the San Francisco Bay Area were selected as locations for our vertiport stations. In order to augment the existing transportation systems, BART and CalTrain routes and ridership statistics were taken into account on these locations. A hub-and-spoke system was selected as the topology to be modeled by RAPTOR. The Santa Clara station was selected as the primary hub due to its position relative to the San Jose International Airport and its centrality to all other designated stations. Quadcopters will operate in Class G airspace to adhere to FAA regulations, following all laws, guidelines, and other necessary components. Further, NorCal TRACON protocol was also researched, as it will be responsible for routing quadcopters on a specific course. The simulation software, Simio, is being utilized to evaluate the theoretical quadcoptor network. Generated models visually depict the numerous maneuvers performed in the experimental studies. Quadcoptor route cruise time, vehicle sequencing, and processing logic were edited to establish real-world phenomenon. The software will also be used for future analyses. We used the computer-aided drafting software called Rhino to develop a model of the full-scale vehicle. The mission capability, vehicle weight, and rotor characteristics, such as diameter and number of blades, were results of an iterated solution from the NASA Design and Analysis of Rotorcraft sizing tool. The quadcoptor design was influenced by the initial vertiport concept. Passenger boarding is done via a towered docking structure, which transfers a pod-like structure between the docked vehicle at the top of the tower and the ground. This design limits the amount of ground noise introduced into the area. The interior vehicle architecture of the quadcopter was designed to showcase how passengers would navigate about the cabin. Seating restraints, interactive screen displays, luggage bays, and bicycle racks are some of the various features included in the design. We hope you ve enjoyed this top-level presentation of Team RAPTOR. If you would like to stay up to date on the progress of RAPTOR, please check http://academy.arc.nasa.gov/aeronautics/ for updates. Thank you.