能走能飞是大自然的典型性特点——很多飞禽、虫类和别的小动物都能保证这个方面。假如人们能让智能机器人具备相近的多功能化，它将打开很多概率:想像一下，设备能够飞进工程建筑地区或不挨近路面的震区，随后挤过路面上的窄小室内空间，运输物块或抢救。
难题是，善于一种交通出行方法的智能机器人一般 不善于另一种。机载无人飞机迅速灵便，但一般 电池循环次数比较有限，没法开展远距离航空。另一方面，路面车子的能耗等级更高，但速率变慢，操控性更差。
来源于麻省理工大学电子信息科学和人工智能技术试验室(CSAIL)的科学研究工作人员正着眼于开发设计即能在陆上上机动性又能飞上天上的智能机器人。在一篇新毕业论文中，该团队展示了一个由8架四轴飞行器构成的系统软件，该系统软件能够在一个相近大城市的自然环境中航空和安全驾驶，并下设停车场、禁飞区和直升机停机坪。
这篇毕业论文的第一创作者、博士研究生布兰登·阿拉基(BrandonAraki)说，航空和安全驾驶的工作能力在有许多 阻碍物的自然环境中很有效，由于你能掠过路面阻碍物，还可以在头上阻碍物下安全驾驶。一般的无人飞机没办法在路面上机动性。一架有车轮子的无人飞机的操控性更强，而航空時间只能轻度的减少。
Araki和CSAIL负责人DanielaRus，及其麻省理工大学本科毕业JohnStrang,SarahPohorecky,CelineQiu，和苏黎世联邦政府理工大学高級交互方式试验室的TobiasNaegeli合作开发了这一系统软件。
这是怎样工作中的，该新项目创建在荒木以前的工作中基本上，开发设计了一个“会飞的小猴子”智能机器人，它能够爬取、爬取和航空。尽管小猴子智能机器人能够绕过阻碍物，四处爬取，但它依然没法独立走动。
以便处理这一难题，该精英团队开发设计了各种各样优化算法优化算法，致力于保证无人飞机不容易相碰。以便让他们可以安全驾驶，科学研究工作组在每架无人飞机的底端装上2个带车轮子的小马达。在仿真模拟中，这种智能机器人能够在充电电池耗光以前航空90米或安全驾驶252米。
在无人飞机上加上驱动器部件后，它的电池循环次数略微减少，这代表它的较大航空间距降低了14%，降到300英寸上下。可是，因为安全驾驶依然比航空高效率得多，因而，安全驾驶高效率的提升填补了因为超载而导致的相对性较小的航空高效率损害。
罗格斯大学(RutgersUniversity)电子信息科学专家教授余京金(音)说，此项工作中为规模性、混和方式的交通出行出示了一个优化算法解决方法，并显示信息出它对实际难题的可接受性。余京金沒有参加此项科学研究。
该精英团队还应用平时原材料检测了该系统软件，如用以路面的纺织物和用以工程建筑的纸箱子。她们检测了8个在无撞击相对路径上从起始点到终点站的智能机器人，全部智能机器人都取得成功了。
罗斯说，像她们那样的系统软件说明，生产制造安全性合理的飞行汽车的另一种方式 并不是简易地在车上安裝飞机翼，只是在很多年的科学研究基本上提升无人飞机的安全驾驶工作能力。
当你刚开始开发设计飞行汽车的整体规划和控制系统时，人们被在小范围之内造就具备这种工作能力的智能机器人的概率所鼓动，罗斯说。尽管要扩张到真实能载客的代步工具显而易见仍遭遇极大试炼，但将来飞行汽车将为人们出示迅速、无交通出行的代步工具，这一发展潜力鼓动了人们。
英文版
English version
Walking and flying is a typical characteristic of nature-many birds, insects and other small animals can guarantee this aspect. If people can make intelligent robots with similar multifunctionality, it will open up a lot of possibilities: Imagine that the device can fly into the engineering construction area or the seismic area not close to the road, and then squeeze through the narrow indoor space on the road to transport objects Block or rescue.
The problem is that intelligent robots that are good at one method of transportation are generally not good at another. Airborne unmanned aircraft is fast and convenient, but the number of battery cycles is generally limited and it is impossible to carry out long-distance aviation. On the other hand, road vehicles have higher energy consumption levels, but their speeds are slower and their handling is worse.
Scientific research staff from the Massachusetts Institute of Technology's Electronic Information Science and Artificial Intelligence Technology Laboratory (CSAIL) is focusing on the development and design of intelligent robots that can maneuver on land and fly to the sky. In a new graduation thesis, the team showed a system software consisting of 8 quadcopters. The system software is capable of aeronautical and safe driving in a natural environment close to a big city. It also has a parking lot, no-flying Zone and helipad.
The first author of this graduation thesis, PhD student Brandon Araki, said that the working ability of aviation and safe driving is effective in a natural environment with many obstacles, because you can pass over road obstacles You can also drive safely under obstacles on your head. General drones cannot maneuver on the road. A wheeled drone is more manoeuvrable, and aviation time can only be reduced slightly.
Araki and CSAIL principals Daniela Rus, and their MIT undergraduates JohnStrang, Sarah Pohorecky, CelineQiu, and Tobias Naegeli of the Federal Government Institute of Technology Zurich's Advanced Interaction Laboratory developed this system software.
How does this work
The new project was created based on Araki's previous work. Basically, a "flying little monkey" intelligent robot was developed and designed to crawl, crawl and fly. Although the little monkey intelligent robot can bypass obstacles and crawl around, it still cannot move independently.
In order to deal with this problem, the elite team developed and designed a variety of optimization algorithms and optimization algorithms, dedicated to ensuring that UAVs are not easy to collide with. In order to make them safe to drive, the scientific research team installed two small motors with wheels on the bottom of each drone. In the simulation, this intelligent robot can fly 90 meters or safely drive 252 meters before the rechargeable battery runs out.
After adding driver components to the drone, its battery cycles have been slightly reduced, which means that its larger aerospace has been reduced by 14% to 300 inches. However, because safe driving is still much more efficient than aviation, the increase in safe driving efficiency has filled the relatively small damage to aviation high efficiency caused by overload.
Yu Jingjin, a professor of electronic information science at Rutgers University, said that in this work, an optimized algorithm solution was presented for large-scale, mixed-mode transportation, and the information showed that it was acceptable for practical problems. Sex. Yu Jingjin did not participate in this scientific research.
The elite team also tested the system software using usual raw materials, such as textiles for pavement and cardboard boxes for engineering construction. They tested eight intelligent robots from the starting point to the end station on a collision-free relative path, and all of them were successful.
Rose said that system software like them shows that another way to make a safe flying car is not to simply install an aircraft wing on the car, but to basically improve the safety of unmanned aircraft in many years of scientific research Driving ability.
When you first started developing the overall planning and control system for flying cars, people were inspired by the probability of creating intelligent robots with this capability in a small area, Ross said. Although it is obvious that it will continue to undergo great trials to expand to a real passenger-carrying vehicle, flying cars will show people a rapid and traffic-free vehicle in the future, and this development potential has inspired people.
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