DAX 自動化提供來自包括科爾摩根在內(nèi)的眾多制造商的數(shù)千種 CNC、伺服電機和驅動部件，以提供圓形和線性定位精度和速度控制，以滿足您的特定應用。

科爾摩根AKM伺服電機擁有廣泛的標準產(chǎn)品，為您提供了選擇和靈活性 – 這些產(chǎn)品經(jīng)過優(yōu)化與科爾摩根伺服驅動器配合使用，可提供卓越的性能以滿足您的應用需求。

科爾摩根的無刷伺服電機產(chǎn)品在業(yè)界市場有出色的性能及靈活性?；贏KM系列標準伺服電機，科爾摩根為低溫應用場合研發(fā)了耐低溫伺服電機，適應低至-40ºC的極寒環(huán)境使用。

 

機器人已經(jīng)比許多人意識到的要廣泛得多。它們現(xiàn)在對許多行業(yè)至關重要，為創(chuàng)新帶來了新的機遇和途徑。從機器人中獲益多的行業(yè)之一是交通運輸。

 

在制造業(yè)之外，機器人技術在交通運輸中的應用是一個相對較新的現(xiàn)象。盡管相對新穎，但機器人已經(jīng)在運輸行業(yè)取得了長足的進步，推動了多個子行業(yè)和應用的創(chuàng)新。沒有機器人，現(xiàn)代交通就不一樣了，未來只會鞏固這一點。

 

以下是機器人如何推動運輸業(yè)向前發(fā)展，以及它們可以從這里走向何方。

自動駕駛汽車

機器人推動交通創(chuàng)新的標志性的例子可能是自動駕駛汽車。雖然全自動駕駛汽車尚未成為現(xiàn)實，但自動化功能已經(jīng)為當今的汽車帶來了重大改進。自動制動、車道修正和自適應巡航控制都是當今車輛中機器人控制的例子。

 

自動緊急制動已將配備它的汽車的后部碰撞減少了 50%。這些系統(tǒng)依靠機器視覺等機器人技術來識別和響應障礙物。然后，他們將整個車輛變成一種機器人，無需人工輸入即可行動。

 

今天阻礙全自動汽車的是機器人技術還不夠先進。他們的人工智能 (AI) 系統(tǒng)必須非?？焖俚刈龀鲰憫词箤τ跈C器人也是如此，并且在變化和不可預測的情況下始終如一地執(zhí)行。隨著機器人的進步和這些目標的實現(xiàn)，真正的自動駕駛汽車將成為日?，F(xiàn)實。

 
 

雖然完全機器人乘用車已被證明是一個挑戰(zhàn)，但自動化公共交通可能更容易。公共汽車、火車和班車遵循固定路線，提供了當今機器人良好運行所需的可預測性。他們通常還會在專用空間中行駛，從而降低與其他車輛發(fā)生碰撞的風險。

 

德國巴特比恩巴赫市于 2017 年開始測試自動駕駛巴士。，它已完成 10,000 多公里的無人駕駛旅行，搭載約 20,000 名乘客。制造自動班車的公司 EasyMile 已幫助全球城市建立無人駕駛巴士路線。

 

2019 年，一列自動駕駛列車在 48 英里的軌道上牽引 30 輛貨車，展示了無人駕駛列車的潛力。隨著美國希望擴大其鐵路系統(tǒng)并使其現(xiàn)代化，自動駕駛列車可能會變得司空見慣。早期制動等人工智能功能也可以使鐵路旅行更安全。

 

雖然自動駕駛汽車可能是機器人在交通運輸中令人興奮的應用，但它們遠非。運輸行業(yè)中機器人技術更常見的用例是在制造車輛的制造中心。自動化已成為汽車制造的關鍵部分，可實現(xiàn)更高的產(chǎn)量。

 

Tesla Gigafactory 在機器人技術使用方面處于行業(yè)地位，某些部分實現(xiàn)了 90% 的自動化，幾乎不需要人工輸入。這種高水平的自動化使工廠能夠在創(chuàng)紀錄的時間內(nèi)生產(chǎn)出技術復雜的車輛，以滿足高需求。考慮到特斯拉 Cyber ??truck在一個月的預購量如何超過 250,000輛，這種速度至關重要。

 

更快的生產(chǎn)時間也讓汽車制造商在更短的時間內(nèi)推出新車型。因此，他們可以生產(chǎn)出創(chuàng)新、并將其交到駕駛員手中，而這個想法仍然是新的和令人興奮的。

 

Robots are already far more widespread than many people realize. They’re now essential to many industries, unlocking new opportunities and avenues for innovation. One of the sectors that stands to gain the most from robots is transportation.

 

Outside of manufacturing, the implementation of robotics in transportation is a relatively recent phenomenon. Despite this relative novelty, robots have already made significant strides in the transportation industry, driving innovation across multiple sub-sectors and applications. Modern transportation wouldn’t be the same without robots, and the future will only serve to solidify this.

 

Here’s how robots are pushing the transportation industry forward and where they could go from here.

 

Self-Driving Cars

Perhaps the most iconic example of robots driving innovation in transport is self-driving cars. While fully autonomous vehicles are not yet a reality, automated features have already brought significant improvements to cars today. Automatic braking, lane correction, and adaptive cruise control are all examples of robotic control in today’s vehicles.

 

Automatic emergency braking has cut rear collisions by 50% in cars that have it. These systems rely on robotic technologies like machine vision to recognize and respond to obstacles. They then turn the entire vehicle into a type of robot, acting without human input.

 

The only things holding back fully autonomous cars today are robotic technologies that are not yet advanced enough. Their artificial intelligence (AI) systems have to respond remarkably quickly, even for a robot, and perform consistently in varying and unpredictable situations. As robots advance and these goals become possible, true self-driving cars will become a daily reality.

 

Autonomous Public Transport

While fully robotic passenger vehicles have proved a challenge, automating public transit may be easier. Buses, trains, and shuttles follow fixed routes, providing the predictability that robots today need to perform well. They also typically travel in dedicated spaces, reducing the risk of collision with other vehicles.

 

The city of Bad Birnbach, Germany, started testing an autonomous bus in 2017. Within the first year, it had completed more than 10,000 kilometers of driverless travel, carrying around 20,000 passengers. EasyMile, the company that made the autonomous shuttle, has since helped cities across the globe establish driverless bus routes.

 

In 2019, an autonomous train pulled 30 freight cars across 48 miles of track, showing the potential of driverless trains. As the U.S. looks to expand and modernize its rail system, autonomous trains could become commonplace. AI features like early braking could make rail travel safer, too.

 

Faster Production

While autonomous vehicles may be the most exciting application of robots in transportation, they’re far from the only one. A more common use case for robotics in the transport industry is in the manufacturing centers that build vehicles. Automation has become a critical part of car manufacturing, enabling higher output.

 

The Tesla Gigafactory leads the industry in robotics use, with some sections being 90% automated, requiring almost no human input. This high level of automation lets the factory produce its technologically complex vehicles in record time to meet high demand. Considering how the Tesla Cybertruck sold more than 250,000 preorders in its first month, that speed is essential.

 

Faster production times also let automakers roll out new models in less time. As a result, they can produce innovative, cutting-edge designs and get them in drivers’ hands while the idea is still new and exciting.