Autonomous Vehicles

What we do

 

We develop optimal solutions for Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles (AV). Our team has acquired unique expertise in computer vision algorithms, mathematical models for deep machine learning, data set conditioning and cloud infrastructures. These transverse skills allow us to provide the right solutions using the right technology that fit the constraints of real time and embedded applications.

We have in-depth knowledge of embedded platform solutions, as well as vision, lidar and radar technologies.  This allows us to achieve increased performance at low power consumption when using dedicated HW on-chip accelerators to integrate and optimize algorithms on target platforms.

As an example, we implemented a pedestrian detection function based on aggregated channel feature (ACF) on an automotive embedded platform using the hardware accelerators available. This resulted in a 12 fold runtime improvement over the same implementation on an Arm® Cortex® -A53 processor.

Our professional services allow our worldwide customer base to benefit from our advanced R&D expertise in this field.

eSoftThings is a member of the Renesas R-Car™ consortium, specialised in the Renesas autonomy™ Platform.

Our products

 

We build and condition datasets, create mathematical models to implement algorithm IP blocks for autonomous driving applications. These algorithms are optimized to address real-time and embedded constraints in order to meet the performances required by our customers on different platforms.

Professional services

 

We benchmark platforms to help our customers select the right solution to meet the performance requirements of their use cases.

Our team integrates and optimizes algorithms on embedded Platform solutions by utilizing the Platform dedicated on-chip accelerators to provide high performance at low power consumption.

We deliver high quality training on embedded Platforms for ADAS.

Use cases

Surround view
application

Front view
application

Driver monitoring
application

• Detection and classification of the environment

• Semantic analysis and cognitive analysis

• Sensor fusion