New Approaches To Sensors And Sensing


Sensors are becoming more intelligent, more complex, and much more useful. They are being integrated with other sensors in sensor fusion, so a smart doorbell may only wake up when it’s imperative to see who’s at the door, and a microphone may only send alerts when there are cries for help or sounds of glass breaking. Kim Lee, senior director of system applications engineering at Infineon, t... » read more

Confusion Grows Over Sensor Fusion In Autos


A key strategy for fully autonomous vehicles is the ability to fuse together inputs from multiple sensors, which is essential for making safe and secure decisions, but it's turning out to be much harder than first imagined. There are multiple problems that need to be solved, including how to partition, prioritize, and ultimately combine different types of data, and how to architect the proce... » read more

Solving The Last-Mile Delivery Problem


Retailers are deploying robots to cut costs and improve efficiency, opening new opportunities for chipmakers as well as a host of new challenges. Key to this strategy are autonomous roadside delivery robots (ARDRs). Retailers have been facing razor-thin profit margins for years and have turned their sights to increasing operational efficiency to stay competitive. Solving the last-mile delive... » read more

How Many Sensors For Autonomous Driving?


With the cost of sensors ranging from $15 to $1,000, carmakers are beginning to question how many sensors are needed for vehicles to be fully autonomous at least part of the time. Those sensors are used to collect data about the surrounding environment, and they include image, lidar, radar, ultrasonic, and thermal sensors. One type of sensor is not sufficient, because each has its limitation... » read more

Machine Vision Plus AI/ML Adds Vast New Opportunities


Traditional technology companies and startups are racing to combine machine vision with AI/ML, enabling it to "see" far more than just pixel data from sensors, and opening up new opportunities across a wide swath of applications. In recent years, startups have been able to raise billions of dollars as new MV ideas come to light in markets ranging from transportation and manufacturing to heal... » read more

Building the Metaverse, Part Two: The Technology


In my first article on the metaverse, I explored the extraordinary vision and driving forces behind the metaverse, along with some potential use cases. In this second part, I want to outline the technology that will be needed to enable it. The metaverse will rely on a range of existing and new hardware and software technologies, which will enable the development of new services and new ways ... » read more

Data Fusion Scheme For Object Detection & Trajectory Prediction for Autonomous Driving


New research paper titled "Multi-View Fusion of Sensor Data for Improved Perception and Prediction in Autonomous Driving" from researchers at Uber. Abstract "We present an end-to-end method for object detection and trajectory prediction utilizing multi-view representations of LiDAR returns. Our method builds on a state-of-the-art Bird's-Eye View (BEV) network that fuses voxelized featur... » read more

Unknowns Driving Up The Cost Of Auto IC Reliability


Automotive chipmakers are considering a variety of options to improve the reliability of ICs used for everything from sensors to artificial intelligence. But collectively they could boost the number of process steps, increase the time spent in manufacturing and packaging, and stir up concerns about the amount of data that needs to be collected, shared, and stored. Accounting for advanced pro... » read more

Data Association Between Perception and V2V Communication Sensors


Abstract: "The connectivity between vehicles, infrastructure, and other traffic participants brings a new dimension to automotive safety applications. Soon all the newly produced cars will have Vehicle to Everything (V2X) communication modems alongside the existing Advanced Driver Assistant Systems (ADAS). It is essential to identify the different sensor measurements for the same targets (... » read more

Multi-View Fusion of Sensor Data for Improved Perception and Prediction in Autonomous Driving


Abstract "We present an end-to-end method for object detection and trajectory prediction utilizing multi-view representations of LiDAR returns. Our method builds on a state-of-the-art Bird's-Eye View (BEV) network that fuses voxelized features from a sequence of historical LiDAR data as well as rasterized high-definition map to perform detection and prediction tasks. We extend the BEV network ... » read more

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