Innoviz and Whale Dynamic partner on LiDar-enabled autonomous driving platform
Whale Dynamic’s L4 autonomous driving platform will feature InnovizOne LiDAR sensors
Innoviz Technologies has announced Whale Dynamic will equip its autonomous driving system with solid-state InnovizOne LiDAR sensors.
Whale Dynamic's autonomous driving (AD) platform identifies and interprets vehicles’ changing environments to provide intelligent driving suggestions. It’s equipped with drive-by-wire technology, making it an ideal plug-and-play solution for robo-taxi and autonomous delivery companies, among other full-stack autonomous service providers.
Per reports, the next-gen Whale Dynamic AD platform will feature low-power InnovizOne LiDARs in place of InnovizPro LiDAR used in the previous versions.
InnovizOne is a solid-state LiDAR sensor that can endure high temperatures and bright sunlight. Pairing the sensor with Innoviz's perception software provides unrivaled angular resolution in object detection, classification, and tracking.
InnovizOne stores and returns multiple reflections per pixel. This is of particular importance when a laser pulse simultaneously strikes multiple objects, such as rain droplets and snowflakes.
InnovizOne LiDARs can be integrated with Level 3, 4, and 5 autonomous vehicles. The sensors' detection range is 0.1 to 250 meters with 115° x 25° (H x V) maximum field of view. As for security, InnovizOne is ISO 9001:2015-certified and adheres to ISO 26262 safety regulations.
"We are excited to expand our technology collaboration with Whale Dynamic to bring Innoviz's advanced high-resolution solid-state LiDAR technology to their AD Platform," said Omer Keilaf, CEO and co-founder of Innoviz.
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"We look forward to collaborating with Whale Dynamics to bring Innoviz's High-Performance LiDAR to L4 Platforms in China, the largest vehicle market in the world."
Whale Dynamic CEO and founder David Chang stated, "InnovizOne brings us more possibilities to create the world's best sensor fusion design and will also empower our perception algorithm to an unprecedented level. We are looking forward to working together to achieve the goal of building a fully autonomous vehicle capable of completing daily service tasks on public roads."
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