Air-borne auto-driving vehicles, which are common in San Francisco, are either waiting to be picked up or travelling to more distant stations for charging and cleaning. Such empty miles without passenger income have been one of the difficulties in compressing the costs and increasing profitability of robotaxi operations.

Aseon Labs tried to address the problem from the infrastructure. The original company, located in Manwood City, California, proposed an automated module close to the size of the parking space, which could be deployed at different locations in the city, to complete inspections, car cleaning and charging for robotaxi. TechCrunch reported that the company had completed $10 million in seed ship financing.

Funds will be used for prototypes and sites

This round of financing was led by Crane Venture Partners, with the participation of Y Combinator, Expa, Robin Hood Ventures and Founders Capital, and some angel investors. Aseon Labs is still in its early stages.

  • Planned construction of 5 prototype automated sites
  • The team will expand from 6 to approximately 12
  • Simultaneous acquisition of site resources for network development

The co-founder and CEO George Kalligeros stated that vehicle utilization must continue to increase if auto-driving taxis were to be brought closer to the economy of the Internet. The goal of the distributed site is to reduce the number of vehicles travelling at long distances for maintenance purposes.

Attempted to replace the outer-native concentration station.

The two founders were not from the auto-driving industry, but had experience in the expansion of hardware and site networks. Kalligeros worked in Bentley and Tesla, and then joined with the co-founder, Dan Keene, who founded the battery replacement infrastructure company Pushme in 2016, which was acquired by Tier Mobile in 2020.

Following a study of the auto-driving industry, the team found that robotaxi operators often relied on centralized sites for inspection, maintenance, cleaning and charging. Owing to the high cost of the site, these facilities are often located on the outskirts of the city, while the main demand for vehicles is concentrated in the centre of the city, which will further stretch the distance.

Aseon Labs therefore chooses a smaller, stand-alone, mobile modular site. Such facilities could be deployed as temporary structures, as envisaged by the company, thus reducing the approval cycle; if a point was under-utilized, it could also be relocated.

There's still work to be done early. AI is responsible for identifying problems.

These sites will be equipped with cameras and mechanical arms. The cameras are used to check the state of the vehicle and the mechanical arm can handle the missing items and complete the cleaning of the base vehicle. In the form of electricity, the equipment can use both propane generators and access existing power sources by working with electric vehicle charging enterprises.

Aseon Labs expects that the site will eventually be autonomous, but the early version will be staffed. The company does not intend to allow the equipment to handle all the complexities, but rather to use the computer visualization and AI model to determine the type of problem before deciding whether to leave it to manual processing.

For example, if the system recognizes melted chocolate in the back seat, the mechanical arm will not be cleaned directly in order to avoid spreading the stain. The vehicle will be charged first and then moved back to the hub station, manually processed.

Additional information:To date, Aseon Labs has not signed a formal contract with any robotaxi, but the company claims that there is a high level of industry interest in this programme.