• Quanergy M1™ LiDAR 360° field of view, long-range and accurate detection enables Vecna’s advanced navigation while eliminating blind spots • Ultra-reliable solution for demanding and dynamic industrial environments • Vecna CPJ Co-bot Pallet Jack to deliver a true co-bot solution empowering the material handling industry to overcome dire labor shortages

SUNNYVALE, Calif. & WALTHAM, Mass. (March 28, 2022) --Quanergy Systems, Inc. (NYSE: QNGY), a leading provider of LiDAR sensors and smart 3D solutions, today announced its M1 LiDAR sensors have been chosen by Vecna Robotics to deliver natural feature navigation for their new Vecna CPJ autonomous co-bot pallet jack.

"Quanergy's M1 LiDAR sensors are key to achieving our objective of democratizing the adoption of robots in the material handling space," said Zachary Dydek, Chief Technology Officer at Vecna Robotics. "The cost-effective, industrial-grade sensors enable our robots to navigate quickly while co-working with humans using seamless touch-and-go automation, helping our customers overcome labor shortages and create a safer, more efficient warehouse."
Vecna CPJ leverages Quanergy's M1 LiDAR sensors for natural feature navigation to help bring automation to long-ignored material handling workflows like pallet and tote consolidation, pick-to-packout, and QA/QC/rework. LiDAR uses time-of-flight sensing to generate rich point cloud data about the surrounding area, allowing the co-bot to navigate the warehouse autonomously abandoning the need for expensive and inflexible beacons.
The use of LiDAR enables the co-bot to collaborate with human partners. For example, the vehicle navigates the warehouse independently, reducing the labor burden while increasing efficiency, uptime and safety.
M1 LiDAR sensors from Quanergy provide best-in-class measurement accuracy, a 360° field of view, and industry leading sensing range. In addition, M1 LiDAR sensors deliver reliable performance even in harsh industrial environments independent of lighting conditions.
"LiDAR is driving the future of robotics, and we're excited to be the ‘eyes' of co-bots like Vecna's autonomous co-bot pallet jack," said Enzo Signore, Chief Marketing Officer at Quanergy. "Where LiDAR was once expensive and unattainable for many, we're now bringing this technology to the masses with cost-effective solutions that unlock the power of LiDAR and democratize the adoption of these robots."
To see Vecna's new co-bot pallet jack in action, visit their MODEX demo booth #B8837 or go to www.vecnarobotics.com. For more information, visit www.quanergy.com or see us in person at MODEX #B4732.

About Quanergy Systems, Inc.
Quanergy's (NYSE: QNGY and QNGY.WS) mission is to create powerful, affordable smart LiDAR solutions for automotive and IoT applications to enhance people's experiences and safety. Quanergy has developed the only true 100% solid-state CMOS LiDAR sensor built on optical phased array (OPA) technology to enable the mass production of low-cost, highly reliable 3D LiDAR solutions. Through Quanergy's smart LiDAR solutions, businesses can now leverage real-time, advanced 3D insights to transform their operations in a variety of industries including industrial automation, physical security, smart cities, smart spaces and much more. Quanergy solutions are deployed by nearly 400 customers across the globe. For more information, please visit us at www.quanergy.com.

About Vecna Robotics
Vecna Robotics is an award-winning flexible, intelligent material handling automation company with solutions engineered for seamless work between autonomous mobile robots (AMR) and the labor, equipment, facilities, and systems that make business go. Our self-driving fork trucks, pallet trucks, pallet jacks, and tuggers -- powered by proprietary Pivotal™ orchestration software and our 24/7/365 command center -- help distribution, warehousing, and manufacturing organizations automate their most critical workflows, maximize throughput and scale operations fast. For more information, visit www.vecnarobotics.com. Follow us on Twitter and LinkedIn.