Mobilis Robotics develops an AI-powered autopilot system for electric wheelchairs, utilizing 3D cameras and video feeds to create a 3D map of the user's environment for collision avoidance and automated navigation. This technology enhances mobility for individuals with limited movement, providing a safer and more efficient means of transportation in indoor spaces.
Funding
$1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Individuals with mobility impairments often face challenges navigating indoor environments safely and efficiently using electric wheelchairs. Current electric wheelchairs may lack advanced features for collision avoidance and automated navigation, increasing the risk of accidents and limiting independence.
Solution
Mobilis Robotics offers an AI-powered autopilot system designed to enhance the mobility of electric wheelchair users. The system utilizes 3D cameras and video feeds to construct a real-time 3D map of the user's surroundings, enabling advanced collision avoidance and automated navigation capabilities. This technology transforms standard electric wheelchairs into intelligent personal mobility platforms, providing a safer and more efficient means of transportation within indoor spaces. The autopilot system offers multiple levels of automation, ranging from basic collision prevention to fully autonomous indoor navigation, and integrates with the user's smartphone or smartwatch for seamless control and monitoring.
Target Audience
The primary target audience includes individuals with mobility impairments who use electric wheelchairs, as well as healthcare providers and caregivers seeking to improve the safety and independence of their patients or loved ones.
Features
- 3D camera and video feed-based environment mapping for real-time obstacle detection
- AI-powered algorithms for autonomous navigation and path planning
- Multiple levels of automation, from collision avoidance to full autonomous driving
- Integration with user's smartphone and smartwatch for control and monitoring
- Self-learning algorithms and neural networks for continuous improvement of navigation capabilities