EXYN技术实现高级自主导航

Exyn Technologies正在开发名为Exynai的全栈软件，该软件可以在复杂的商业环境中为机器人提供自动导航和实时映射。

One of the biggest challenges in robotics is developing autonomous systems that can reliably operate in unmapped environments. This is why, for example, leading self-driving car company Waymo only tests in areas it’s spent countless hours at creating detailed 3D maps.

Exyn技术, a spin-off of the University of Pennsylvania’s GRASP lab founded by Vijay Kumar, is making tremendous in-roads in autonomous navigation and real-time mapping of unfamiliar, infrastructure-less environments that don’t have beacons, GPS or ultrawideband technology. The technology works just as well in environments equipped with infrastructure, but that’s old-hat at this point.

The Philadelphia startup, which took part in our inaugural机器人峰会和展示、正在开发可伸缩的完整软件调用ed exynAI that enables autonomous navigation and real-time mapping for Autonomous Aerial Robots (A3R) in complex commercial environments. At the moment, Exyn is focusing on indoor drone applications, including construction, logistics and mining. But the technology can also work on ground-based robots. In fact, Exyn is currently working with a legged robotics company, but it can’t publicly disclose the name of its partner just yet.

Exynai的工作原理

So how does it work? Exyn co-founder Nader Elm said the key to enabling autonomous navigation starts with these questions:

我在环境中在哪里？
Where am I trying to go?
How do I get there optimally?

Exyn uses multiple sensors to perceive its environment – cameras, LiDAR (Velodyne VLP-16), radar, and RGBD – and late-stage sensor fusion that compiles the data in real time to estimate a robot’s position and orientation relative to where it started. The VLP-16 is the primary sensor for SLAM and for part of the system’s SLAM and state estimation capabilities. “Each sensor gives state estimation, then we fuse it,” Elm said. “Depending on the confidence level of each sensor, we’ll use it. If it’s low confidence, we consider it bad data and get rid of it.”

在下面查看Exyn的视频，展示了其在矿山中的自动飞行功能。根据Exyn的说法，该路线没有预先编程，人类飞行员没有操纵控件，并且实时在无人机上进行处理。

Elm说，困难的部分正在建立AI，该AI帮助A3R了解他们在3D中看到的环境。Exyn使用机器学习和深层神经网络来做到这一点。“这是Google一直在努力十年的困难部分。Google正在做什么使汽车无人驾驶，我们正在为无人机做什么。Exyn具有利用Upenn十年的研究的优势。”

“As the drone is moving and obstacles dynamically appear in its path — a forklift or a person — you need to dynamically change the path. We can do that in real time with onboard processing,” Elm said. “But now, using machine learning, we can identify what’s in front of the drone and change the behavior of the drone based on what it is. If it’s a forklift, for example, go around it and complete mission. If it’s a person, come to a stop and stay a safe distance away. These are new and exciting things we’re integrating into our stack – semantic labeling of objects in the drone’s path.”

Exyn表示，可以定制Exynai软件是特定于任务的并支持群。它还提供了自主权的“滑动规模”，从完全自主的航班到自动驾驶和飞行员辅助的航班，避免了障碍。

Why Exyn started with indoor drones

Exyn’s technology appears to be a fit for a number of outdoor drone applications, too. But on-going battles over outdoor, commercial drone regulations have been a turnoff for the company.

“Regulations really constrain outdoor drone applications,” said Elm. “Regulations don’t really exist for indoor drones. Fortune 500 companies will have policies, and we are mindful of people and safety policies in warehouses. Indoor drones are unregulated, but not unrestricted.”

Two of Exyn’s main competitors, Near Earth Autonomy (NEA) and Skydio, both focus heavily on outdoor applications. Skydio’s R1 is a consumer drone billed as a “flying camera,” while NEA has built systems to inspect agricultural environments, power plants, and many other outdoor areas. Other potential competitors include Airobotics and Iris Automation.

Indoor Applications

Elm said Exyn technology is currently in the pilot stage, “looking to put more miles on the system and make it even more reliable.” Exyn isn’t a drone company, it’s a software company building AI that enables drones to complete tasks without human intervention. The initial three markets for A3R are construction, logistics and mining. Here’s a quick look at each of these applications:

Construction: an inside-out view
由于建筑物的设计方式与实际建筑锅外的方式之间的差异，建筑行业每年都会损失数十亿美元。这导致项目落后于时间表和预算。有些公司从外部建造3D建筑物的3D模型，包括3D机器人技术，但Elm说：“大多数建筑问题发生在里面。”因此，Exyn提供了有关施工问题的内而外的看法。

他说：“随着屋顶甲板的继续，GPS变得不可用，我们可以定期从建筑物内部提供地图和模型，以将AS-IS与设计计划进行比较。”“这使建筑团队可以跟踪进度并找到错误并解决返工。想象一下，大金属梁固定在屋顶上。他们看起来都一样。但是，当屋顶的家伙到达时，他们注意到一束梁太高了，一束梁太小了。现在屋顶弯曲了。这是一个$ 50,000的修复程序，延迟了一周。”

Mine surveying
Mine surveying is a critical task necessary for designing, excavating, and documenting information at all stages of mining. But mines are dangerous environments for humans, and surveying techniques are labor intensive and time consuming.

Exyn’s A3R robots, again with no pre-loaded maps or GPS, can be deployed anywhere within a mine and be used to map the environment and collect data.

“Imagine a robot building a map of a mine on a frequent basis to track layout of mine and 3D models to understand volumes of what’s been extracted?? These are specific pain points in mining that we’re looking to automate for data acquisition.”

Warehouse inventory management

Drones are starting to make their way into warehouses for inventory management applications, and the A3R can communicate in real time with warehouse management systems. For larger sites, collaborative robot swarms can be used to perform inventory management quicker.

埃尔姆说：“仅视觉系统需要灯光保留，这对仓库老板来说并不理想。”“系统还需要在非常狭窄的过道中运行，因此系统需要良好的状态估计。因此，通常这需要基础架构，但我们不需要任何基础架构。

“You’ll be going down aisles and the lights go out. Warehouses are motion activated, and the drones don’t activate the lights. So you need to be able to operate in both types of environments and transition between both environments smoothly.”