肖健雄（人稱Professor X），創(chuàng)辦了無人駕駛公司AutoX。作為80后計算機視覺領域的學術新星，機器視覺領域著名的科學家。肖健雄本碩就讀于香港科技大學，2012年獲得世界頂尖計算機視覺大會ECCV最佳學生論文獎和Google Research最佳論文獎，2013年獲得麻省理工學院博士學位。他在PhD畢業(yè)后直接擔任美國普林斯頓大學計算機科學系Tenure Track助理教授，并從零開始創(chuàng)建了普林斯頓計算機視覺與機器人實驗室。
在普林斯頓期間的短短三年時間，他發(fā)表了三維深度學習的一系列奠基性論文。由于他的杰出學術貢獻和世界級影響力， 他兩度獲得Google Faculty Awards，多次獲得Intel Research Awards 和美國國家自然基金委員會研究獎。他的研究成果被廣泛應用到自動駕駛和機器人等相關領域。2016年他領導的普林斯頓團隊和麻省理工學院聯(lián)合獲得了Amazon Picking Challenge機器人大賽世界第三和第四名。
肖健雄2016年在湖南大學生的一次講座，介紹了自己在解決計算機視覺與機器人感知之間的鴻溝問題上所做的研究，如從運動信息中恢復三維場景結(jié)構(gòu)、3D目標探測等，并介紹了一個新的領域，即三維深度學習，同時分享了該理念在室內(nèi)機器人物體檢測與定位、即時定位與地圖構(gòu)建等方面的應用。與機器人的自動導航功能相似，肖健雄還介紹了能自我判斷、自主導航的自動駕駛技術，并以Google所研發(fā)的無人車Google DriverlessCar為例，介紹了自動駕駛技術的核心——雷達辨識、人工智能判斷、全車技術等，還展示了一種新的基于深度學習的自動駕駛技術模式，其訓練基于駕駛模擬儀器的虛擬圖像，與一般的無人駕駛模式不同，該方法直接學習由輸入圖像到車輛未知和轉(zhuǎn)向的映射。
在肖健雄看來，無人駕駛會是繼PC、互聯(lián)網(wǎng)、智能手機之后的“Next Big Thing”，他認為無人駕駛行業(yè)將會有傳感器提供商、汽車制造商、計算設備提供商等，而AutoX致力于提供無人駕駛的軟件系統(tǒng)，他希望成為AutoX成為無人駕駛時代的操作系統(tǒng)，無人駕駛車的大腦，就像智能手機時代的Android，PC時代的Windows。
肖健雄帶領的團隊在計算機視覺和無人駕駛領域有深厚積累，他們目前的解決方案覆蓋了自動駕駛領域的環(huán)境感知、規(guī)劃以及最后的控制的階段。AutoX雖然創(chuàng)立不久，但是在技術上取得了一系列的重大突破。他們僅使用攝像頭就能實現(xiàn)車輛的自動駕駛，由于無需采用雷達、激光、超聲或者特殊的導航設備，所以能夠大量降低自動駕駛的實現(xiàn)成本。
總結(jié)，AutoX的特點可以用幾個關鍵字表達，三維深度學習（可查看下面鏈接），計算機視覺。
參考的國外文章
In the spring of 2016, Dr. Jianxiong Xiao — affectionately known among students and staff as "Professor X" — said goodbye to his plum professorship at Princeton and his post asthe founding director of the school'sComputer Vision and Robotics Labs.
By the fall of that same year, Xiao, known as something of a risk-taker, had moved himself and his family from New Jersey to Silicon Valley, and raised some modest seed funding for his new startup focused on self-driving cars.
His startup, dubbedAutoX,?has done its best to stay under the radar to date — apart?from afiling with the California DMVto test self-driving vehicles.
The filing officially put the professor's mysterious startup in the company of giants, such as?Tesla, Waymo (formerly the Google self-driving car project), Uber, and numerous other big auto companies testing self-driving cars.
But Xiao isn't worried about getting run over by the giants, saying that his small team of academics possesses the kind of expertise?in computer vision that big corporations just can't match. Exhibit A: after?only six months on the job, Xiao says he's already developed a prototype vehicle?that can do the same things as the cars made by his?deep-pocketed rivals, at a fraction of the cost.
AutoX gave a first peek at its creation on Friday, with a debut video showing its prototype system in action. The car itself isn't anything special in terms of style (it's basically just a regular2017 Lincoln MKZthat's been rigged with AutoX technology), but it deftly navigates residential streets near San Jose, seeming to handle driving situations such as cloudy days and night-time, historically a challenge for self-driving cars, with ease.
As noted in the video, AutoX's system doesn't rely on the LIDAR laser arrays or other expensive sensors that most self-driving cars, including Waymo's and Uber's, require to function. Instead, AutoX uses advanced artificial intelligence to "see" through cameras mounted on the car and steer the car accordingly.
Better yet, Xiao tells Business Insider that the cameras that power this AutoX prototype were purchased at Best Buy for $50 a pop. "It could not be cheaper than that,"?he says.
From Xiao's standpoint, that's a crucial point: While future iterations of AutoX technology will support ultrasonic sensors and LIDAR and all that stuff for the sake of enhancing driver safety, the startup is currently focused on building the cheapest and most accessible system for self-driving cars that it possibly can.
While Waymo's self-driving cars sport cameras to "see" around them, they mostly rely on LIDAR laser arrays and other radar sensors to function.Waymo; Business Insider/ Skye Gould
To Xiao, self-driving cars have the potential to benefit society, from cutting down on traffic, to providing more autonomy for the disabled, to making long-distance trucking safer and more efficient. The next step for AutoX is building out a fleet of test cars, so it?can test the technology with a variety of different vehicles types.
"Self-driving [cars] shouldn't just be a luxury, but be available to every citizen," Xiao says.
Purely academic
Athoughtful speaker,Xiao says he got the nickname Professor X because some of his peers at Princeton?found his actual name "very complicated" (hispersonal web pageincludes a link to hear a sound of how his name is pronounced).
The term for Xiao's specific field of study is "computer vision," a branch of artificial intelligence that's just as applicable to self-driving cars as it is to Snapchat puppy filter selfies.
For Xiao, it's been a long-time area of interest. Over the years, he's won recognition from the likes of Google and Amazon for his and his team's advancements in the field of computer vision. In 2013, Xiao received his PhD from MIT, right before he went to Princeton.
The impetus for going from academia to Silicon Valley was simple, he says: He had long seen self-driving cars as a huge potential market for computer vision. After consulting with his network of computer vision and autonomous driving experts in academia, he decided the time was right to take a big leap and go into business.This readout from an Uber self-driving car shows how it uses a LIDAR laser array to "sense" the world around it. AutoX just uses ordinary cameras in its current form.Uber
It's that academic pedigree?that gives AutoX an advantage, Xiao says, as it "enables us to to tap into the academic research network." With artificial intelligence experts in such high demand in Silicon Valley, it helps with recruiting that Xiao and his team already have personal relationships with many of the best and brightest in the field.
"We've known these people in person for many years," Xiao says.
Nowadays, Xiao says, AutoX is about 20 people strong, almost all engineers, with PhD-level computer vision talent that had previously worked at companies like Apple, Magic Leap, and Microsoft.
And with all that brainpower on board, Xiao says that they were able to build their prototype from scratch in only six months, without using anyone's technology. With the Waymo/Uber self-driving car IP lawsuit rocking Silicon Valley, that's a huge plus.
Xiao says the shift from academia to startup has required a subtle change in how he approaches problems. In academia, you tend to flit from one project to the next. At a private company like AutoX, you "actually make things work, actually get things done" in service of one big idea. In this case, self-driving cars.
Driven to success
While Xiao stresses this system is still a prototype, he does say it indicates the way he wants to see AutoX go, with a focus on building real self-driving technology that can handle every situation, versus more limited driver-assist features like Tesla's autopilot, which canonly be engaged on freeways.
AutoX isn't much interested in manufacturing cars and going head-to-head with Tesla, Xiao says. He's equally uninterested in following thecontroversial Comma.aiinto helping people give their existing cars limited self-driving features.
Instead, Xiao says, he's looking to partner up with auto manufacturers for their future vehicles. AutoX provides the core technology, almost like an operating system, that car companies can then take, customize to their exact needs, and use as the basis for their own autonomous systems.
Residential streets can present a challenge for self-driving cars.Waymo
Additionally, Xiao says that AutoX is similarly looking to license out its software to trucking companies, factory operators, and the like.
Xiao also wants to distinguish between AutoX and the technology from companies likeMobileye, which Intel bought for $15 billion this week?— Mobileye helps self-driving car "see," sure, but other software has to take its perceptions and translate it into action for the car. AutoX is the whole package, says Xiao.
"We're building the brains for self-driving vehicles," Xiao says.
