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RoboSenseAnnounced

RoboSense Phoenix

The RoboSense Phoenix is one of two SPAD-SoC chipsets built on RoboSense's proprietary EOCENE architecture, unveiled on 26 August 2026 alongside the company's H1 2026 interim results. The EOCENE architecture integrates a single-photon avalanche diode (SPAD) array with the receive and signal-processing pipeline on a single die, enabling a digital, single-photon detection path in LiDAR.

On the manufacturer's site Phoenix is presented as the „Phoenix Chipset” with a 2160-beam, 4-megapixel point cloud — positioning that points to a high-resolution LiDAR. RoboSense has not publicly attributed the Phoenix chipset to a specific LiDAR product; the sibling Peacock chipset powers the mass-produced, fully solid-state E2 LiDAR.

Phoenix remains at the unveiling/announcement stage — the manufacturer has not confirmed it in mass production. In the second half of 2026 RoboSense said it will continue to iterate and improve its SPAD-SoC chips built on the EOCENE architecture.

#SPAD-SoC#LiDAR#digital LiDAR#RoboSense#Phoenix#EOCENE#single-photon avalanche diode#SoC
Market classIndustrial

Classification

LiDAR SPAD SoC · serves as: Sensing, Perception.

Which group RoboSense Phoenix belongs to and how it is built

5items
Sensing
Hardware domain
Industrial
Market class

Proprietary integrated circuits for LiDAR — SoCs integrating detectors (e.g. SPAD) and signal processing on a single chip.

System-on-chip for digital LiDAR integrating a single-photon avalanche diode (SPAD) array with the receive and signal-processing pipeline.

A single semiconductor component integrating CPU, GPU, AI accelerators, memory controllers, multimedia engines, and communication interfaces.

Technical specification

What RoboSense Phoenix can detect and measure in its environment

2parameters
Point cloud support
Yes

Time of Flight is the most widely used measurement method in LiDAR sensors. Distance is determined by measuring the time required for a laser pulse to travel to an object and return to the receiver. This approach is broadly used in robotics, autonomy, mapping, and spatial perception systems.

Updated: 28 August 2026