We decided to use Aetina’s hardware due to the build-quality, extensibility, and robustness. No other product line that we considered had such a complete feature set. All of our questions were handled quickly and easily by Aetina support.
— Wilkins White, Sr. Embedded Engineer at Daxbot
The Challenge: General-Purpose Robots
Traditionally, robots with top-down operating systems are programmed for specific tasks and excel in predictable environments, such as industrial robots performing predefined jobs.
Aetina’s client, Daxbot, a pioneering robotics company in the US, created Dax, a general-purpose AI service robot for navigating urban environments and performing various tasks. However, there are challenges inherent in this endeavor:
Autonomous Navigation:
Essential for perceiving and reacting to complex surroundings
Real-Time Robotics Vision:
Needed for obstacle detection, interaction, and sidewalk data gathering.
Composite AI:
Requires integrating various AI techniques and processing neural network tasks efficiently.