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The Exhibitor Console is your XPONENTIAL hub for all the information you need to know – from deadlines to promotional items - in one convenient location.

Important Dates and Information

Virtual Platform Launch

Note: only registered attendees can access the virtual platform and virtual booth. 

September 28, 2020

Virtual Platform Coffee Talk

  • Zoom Link 
  • Meeting ID: 865 9877 2303
  • Passcode: 447699
  • Phone: +1 301 715 8592

October 1, 2020

1:00pm EST

XPONENTIAL 2021 Rebook

Rebook will take place during XPONENTIAL 2020. You will receive an email by Thursday, October 5 with your rebook time. This will be the time that you can log into the system and select your physical booth location for XPONENTIAL 2021 scheduled for Atlanta May 3-6.

October 7-8, 2020

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Hesai Inc.  

Palo Alto,  CA 
United States
http://www.hesaitech.com
  • Booth: Virtual Booth


Hesai looks forward to meeting & engaging with you at AUVSI.

Hesai Technology founded in Shanghai is a global leader and manufacturer of high performance 3D LiDAR sensors. Our innovative development philosophy combines core strengths of industry-leading performance, manufacturability, and reliability. Hesai sensors incorporate our proprietary micro-mirror and waveform fingerprint technologies. Hesai leads the industry in sensor innovations and product adoptions with a 500+ patent portfolio and has become the top LiDAR supplier to robotaxi fleets worldwide and diverse customers in autonomous vehicle, autonomous trucking, robotics, UAV, mapping, smart infrastructure spanning 70+ cities in 20 countries and regions. Hesai has raised over $230M from Bosch, Lightspeed, Baidu and other global investors.


 Press Releases

  • 2020-09-01

    Hesai, a global leader in LiDAR sensors, officially released its next-generation mechanical LiDAR, Pandar128. Designed for automotive volume production, Pandar128 is one of the most advanced mechanical LiDARs available and offers an ideal solution for autonomous driving applications.   

    Pandar128 boasts:

    1. Resolution: up to 0.1° (H) * 0.125° (V) at 10 Hz refresh rate
    2. Up to 6,912,000 points/sec
    3. Detection capability: 200 m (10% reflectivity target)
    4. High reflectivity accuracy and precision
    5. Higher ingress protection rating: IP6K9K

    Pandar128 represents a massive leap in performance over existing mechanical LiDAR sensors. It offers the finest horizontal resolution (up to 0.1°), 1.5x the total points produced by other available 128-channel LiDARs, and has a detection capability of 200 meters @ 10% reflectivity. This unrivaled measurement frequency and distance enable superb perception over an extended range, providing autonomous driving systems with longer reaction time critical for safe operation at medium-to-high driving speeds. 

    Pandar128 is designed with several other noteworthy improvements. It offers a higher level of ingress protection (IP6K9K), ensuring reliability in all weather conditions. Additionally, Hesai’s proprietary, industry-leading interference rejection feature has been further refined, reducing the noise rate. 

    Despite comprising twice the number of beams as Hesai’s Pandar64, Pandar128 retains a small form factor: it is just 7 mm taller and weighs only 1.63 kg. Pandar128’s compact design allows for seamless integration into a vehicle’s exterior for a more aesthetic configuration. The new system architecture also minimizes power consumption, requiring a maximum of 27 W (10 Hz), despite the massive data volume. 

    Most notably, Pandar128 is designed for automotive volume production. It has gone through comprehensive testing and is embedded with several innovative features, such as self-diagnosis for each beam. The sensor data is also encoded to safeguard against data misrepresentation or falsification. Referencing the full array of international automotive standards at the component, product, and process-level, Pandar128 has been meticulously scrutinized and optimized from the ground-up to ensure user safety, system integrity, and reliability. 

    A critical sensor in autonomous driving systems, LiDAR – and its production readiness – is a prerequisite for the large-scale deployment of autonomous vehicles. With Pandar128, Hesai continues to push the boundaries of LiDAR technology and engineering to help achieve this ultimate goal.

    https://www.hesaitech.com/en/media/48

  • 2020-07-09

    High-quality data is the fuel that powers AI algorithms. Without a continual flow of labeled data, bottlenecks can occur and the algorithm will slowly get worse and add risk to the system.

    It’s why labeled data is so critical for companies like Zoox,  Cruise and Waymo,  which use it to train machine learning models to develop and deploy autonomous vehicles. That need is what led to the creation of Scale AI, a startup that uses software and people to process and label image, lidar and map data for companies building machine learning algorithms. Companies working on autonomous vehicle technology make up a large swath of Scale’s  customer base, although its platform is also used by Airbnb, Pinterest and OpenAI, among others.

    The COVID-19 pandemic has slowed, or even halted, that flow of data as AV companies suspended testing on public roads—the means of collecting billions of images. Scale is hoping to turn the tap back on, and for free.

    The company, in collaboration with lidar manufacturer Hesai, launched this week an open-source data set called PandaSet that can be used for training machine learning models for autonomous driving. The data set, which is free and licensed for academic and commercial use, includes data collected using Hesai’s forward-facing PandarGT lidar with image-like resolution, as well as its mechanical spinning lidar known as Pandar64. The data was collected while driving urban areas in San  Francisco and Silicon Valley before officials issued stay-at-home orders in the area, according to the company.

    “AI and machine learning are incredible technologies with an incredible potential for impact, but also a huge pain in the ass,” Scale CEO and co-founder Alexandr Wang told TechCrunch in a recent interview. “Machine learning is definitely a garbage in, garbage out kind of framework — you really need high-quality data to be able to power these algorithms. It’s why we built Scale and it’s also why we’re using this data set today to help drive forward the industry with an open-source perspective.”

    The goal with this lidar data set was to give free access to a dense and content-rich data set, which Wang said was achieved by using two kinds of lidars in complex urban environments filled with cars, bikes, traffic lights and pedestrians.

    “The Zoox and the Cruises of the world will often talk about how battle-tested their systems are in these dense urban environments,” Wang said. “We wanted to really expose that to the whole community.”

    he data set includes more than 48,000 camera images and 16,000 lidar sweeps — more than 100 scenes of 8s each, according to the company. It also includes 28 annotation classes for each scene and 37 semantic segmentation labels for most scenes. Traditional cuboid labeling, those little boxes placed around a bike or car, for instance, can’t adequately identify all of the lidar data. So, Scale uses a point cloud segmentation tool to precisely annotate complex objects like rain.

    Open sourcing AV data isn’t entirely new. Last year, Aptiv and Scale released nuScenes, a large-scale data set from an autonomous vehicle sensor suite. Argo AI, Cruise and Waymo were among a number of AV companies that have also released data to researchers. Argo AI released curated data along with high-definition maps, while Cruise shared a data visualization tool it created called Webviz that takes raw data collected from all the sensors on a robot and turns that binary code into visuals.

    Scale’s efforts are a bit different; for instance, Wang said the license to use this data set doesn’t have any restrictions.

    “There’s a big need right now and a continual need for high-quality labeled data,” Wang said. “That’s one of the biggest hurdles overcome when building self-driving systems. We want to democratize access to this data, especially at a time when a lot of the self-driving companies can’t collect it.”

    That doesn’t mean Scale is going to suddenly give away all of its data. It is, after all a for-profit enterprise. But it’s already considering collecting and open sourcing fresher data later this year.

    https://www.hesaitech.com/en/media/44

  • Chinese LiDAR Sensor Manufacturer Hesai Unveils Blind Spot Detection Technology for Self-Driving Cars

    June 07, 2020 by Luke James

    Chinese Hesai unveils its innovative blind spot detection technology for self-driving cars. The company claims that its technology could “challenge’ industry leaders in the US and Europe.

    Chinese light detection and ranging (LiDAR) technology developer Hesai unveiled its new blind spot detection sensor, the PandarQT, at CES 2020. It is the company’s latest addition to its expansive portfolio of self-driving sensing solutions which the company claims will “challenge” similar products from industry leaders in the United States and Europe such as Ford and Volvo. 

    Blindspot sensing is an important feature of autonomous vehicles (AVs) that detects other vehicles located close to the driver- and near-side. When a vehicle is detected by the sensor, a visual, audible, vibrating, or tactile warning is delivered to alert the driver.

    They may also do more than just monitor the driver- and near-side of a vehicle, such as monitoring the rear or delivering cross-traffic alerts, which alert drivers to an approaching vehicle when backing out of a parking space. 

    Hesai’s New Blind Spot Detecting Technology

    Hesai’s PandarQT blind spot detecting sensor is a 64-channel, ultra-wide FOV LiDAR sensor that features a 104.2° (±52.1°) by 360° ultra-wide Field of View (FOV), making it extremely suitable for vehicle blind spot coverage. 

    According to Hesai, the sensor has been designed specifically to address many of the most common pain points in LiDAR applications and is inclusive of other features such as a compact and aesthetic design, making it easier to incorporate into both existing and future systems. Other features of the PandarQT include unique interference rejection technology that stops interference from nearby working LiDAR systems and support for precision time protocol (PTP) synchronization. 

    Hesai recommends that the PandarQT should be used in combination with its Pandar64. This setup combines PandarQT’s short-range capability and Pandar64’s long-range performance for an all-round, detailed view of a vehicle’s driver- and near-side surroundings. 

    A simulation of the Snapdragon Ride Platform.

    A simulation demonstrating the Snapdragon Ride Platform, which can reportedly offer road visualization. Image credited to Qualcomm

  • Open Bosch Award 2019 - Winner Hesai Photonics Technology

    Media-ID #1858300

    Open Bosch Award 2019 - Winner Hesai Photonics Technology

    The Bosch Group recognizes Hesai Photonics Technology Co., Ltd. with the “Open Bosch Award” for best start-up collaboration. This marks the first time the supplier of technology and services honors outstanding performance in open innovation between Bosch and start-ups. On the picture from left to right: David Li, CEO of Hesai Photonics Technology Co., Ltd., Dr.-Ing. Michael Bolle, CDO and CTO of Bosch, Jumana Al-Sibai, Executive Vice President Bosch Chassis Systems Control

    Reproduction for press purposes free of charge with credit “Picture: Bosch”

  • Chinese LiDAR maker Hesai raises $173M

    Company claims investment round the largest in China’s LiDAR sector.

    While LiDAR manufacturers are busy pumping out new sensors at CES 2020, a leading Chinese LiDAR maker closed one of largest financing rounds in the sector.

    Shanghai-based Hesai Technology raised a Series C round of $173 million. The round was co-led by the German Bosch Group and Lightspeed Ventures, Qiming Venture Partners, ON Semiconductor, DT Capital Partners, Axiom Singapore and others investors.

    Prior to the Series C, Hesai raised more than $150 million from Baidu China and ZhenFund since 2015. The company was established in 2013 in Silicon Valley, but it relocated to China in 2014.

    Hesai’s core products target autonomous vehicle developers. The PandarGT is solid-state LiDAR, while the company’s other four models are mechanical LiDARs. Hesai also makes the Pandora all-in-one sensor kit that integrates cameras, LiDAR and data processing ability (from Baidu Apollo) into the same module for autonomous vehicle developers.

    One its website, Hesai touts various customers, including Bosch, Lyft, Navy, Nuro, TuSimple and more. According to DealStreet Asia, more than 50% of the 65 companies certified to test autonomous vehicles in California are Hesai customers.


 Products

  • PandarXT
    PandarXT is a high resolution 3D LiDAR sensor that is a cost-effective solution designed for multiple different applications, including unmanned logistics, robotics, surveying, security, mapping, and low-to-medium-speed autonomous driving....

  • PandarXT

    PandarXT has a minimum range of zero and outputs valid point cloud even when an object directly touches the sensor’s enclosure. It also has millimeter-level ranging accuracy and superb precision (1σ) of ~0.5 cm. Furthermore, it's improved reflectivity accuracy and greater dynamic range enable accurate and consistent detection of retroreflectors, low-reflectivity targets, and object boundaries with sudden changes in reflectivity. Consistent with every LiDAR in Hesai’s Pandar series, PandarXT has undergone and passed stringent reliability testing to ensure robustness and reliability in any operational environment.

    PandarXT marks a breakthrough in LiDAR system design and its combination of performance, price, and reliability makes it an optimal sensor for numerous LiDAR-powered applications.  

  • Pandar128
    Integrating Hesai’s best-in-class technology and designed in accordance with automotive grade standards, Pandar128 is the most advanced mechanical LiDAR currently available and offers an ideal solution for autonomous driving applications....

  • Pandar128

    Pandar128 boasts:

    • Image-grade resolution: up to 0.1° (H) * 0.125° (V) at 10 Hz
    • Unrivaled point density: up to 6,912,000 points/sec
    • Extended measurement range: 200 m @ 10% reflectivity (70% detection probability, with noise rate below 10-5)
    • High range accuracy and precision: 0.3~1 m: ±5 cm, 1~200 m: up to ±2 cm, RMSE <2 cm
    • High reflectivity accuracy and precision: ±15%, RMSE <10%
    • Superior interference rejection: the noise rate of multiple LiDARs operating together in close proximity is less than 10-5
    • Highest ingress protection grade: IP6K8 & IP6K9K
    • Functional safety: designed to meet ISO 26262 ASIL-B (D)
    • Comprehensive self-diagnostics: Power on self-test & running self-test @ DV≥Medium, 20+ types
    • Cybersecurity: network encryption (designed to meet ISO 21434)
  • PandarQT
    PandarQT is Hesai’s solution to blind spot detection in autonomous driving. It has all the necessary merits of being a blind spot LiDAR – wide vertical field of view, excellent short-range performance, compact size, and a practical range....

  • PandarQT

    This 64-channel, ultra-wide FOV LiDAR is the cutting-edge answer to blind spot detection. It features a 104.2° (±52.1°) by 360° ultra-wide Field of View (FOV) which is ideal for vehicle blind spot coverage.

    With PandarQT, there is much more than what meets the eye. Apart from its compact and aesthetic design, PandarQT boasts a number of features that contribute to its outstanding performance and reliability. Hesai's unique interference rejection technology prevents interference from nearby working LiDARs and thus lowers the false detection rate; PTP (Precision Time Protocol) time synchronization is supported to greatly simplify cabling on vehicles. As with all Hesai LiDARs, each PandarQT unit is checked for range accuracy, precision, and other specs before shipping.

  • Pandar64
    Pandar64 is a 64-channel mechanical LiDAR. It creates 360° 3D images by rotating 64 laser diodes inside the housing. Pandar64 serves a wide range of industries, including autonomous driving, HD mapping and logistics....

  • Pandar64

    Key features of Pandar64 include:

    1. Unique channel distribution tailored for autonomous driving applications: vertical resolution reaches 0.167° in critical fields of view, offering optimal perception results

    2. Extended measurement range: seeing 10%-reflectivity objects from 200 meters away

    3. Interference rejection: undisturbed in the proximity of other working LiDARs

    4. Supporting angle-trigger signal output: achieving multi-sensor hard synchronization with high sync accuracy

    5. Option of PTP time sync simplifies vehicle cabling.

    Pandar64 has gone through stringent reliability tests, including HALT (highly accelerated life test), vibration strength test and mechanical resonance test, ensuring excellent and stable performance in harsh environments.

  • Pandar40P
    Pandar40P is a 40-channel mechanical LiDAR. It creates 360° 3D imaging by rotating 40 laser diodes inside the housing. The unique channel distribution makes it more suitable for autonomous driving applications....

  • Pandar40P

    Pandar40P is marked by three key features:

    1. Interference rejection: undisturbed in the proximity of other working LiDARs

    2. Extended range: seeing 10%-reflectivity objects from 200 meters away

    3. PTP synchronization: option of PTP time sync simplifies vehicle cabling

    Pandar40P has gone through stringent reliability tests, including HALT (highly accelerated life test), vibration strength test and mechanical resonance test, ensuring excellent and stable performance in harsh environments. Pandar40P serves a wide range of industries, including autonomous driving, HD mapping and logistics.


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