CEO
Mentee Robotics
MenteeBot develops personalized, AI-based robotic platforms designed for user interaction and mentorship. These autonomous systems utilize advanced artificial intelligence to adapt and learn from user input. The platform offers a unique, non-teleoperated approach to human-robot engagement.
- Artificial Intelligence
- Robotics
Updated 16 days ago
Funding
Raised to date
$17.2MRaised 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.
across 1 round
DSHA$17M · Series B
Announced Apr 2024
Disclosed cumulative: $17M
RoundDateAmountValuationInvestors
Founders
Product
Problem
The development and deployment of robots capable of performing complex tasks in unstructured, real-world environments is limited by challenges in perception, navigation, and control. Traditional robotics approaches often struggle with adapting to dynamic environments and executing tasks that require fine motor skills and natural language understanding.
Solution
Mentee Robotics is developing MenteeBot, a humanoid robot designed to operate in dynamic environments using advanced AI and robotics technologies. MenteeBot leverages Sim2Real learning to enable lifelike gait and hand movements, allowing it to perform delicate tasks with precision. The robot utilizes NeRF-based real-time 3D mapping and localization for navigation, along with Large Language Models to build a cognitive map of its surroundings and understand natural language commands for task execution. This combination of technologies enables MenteeBot to understand and interact with the world in a more human-like way.
Target Audience
The primary target audience includes businesses and organizations seeking advanced robotic solutions for automation, assistance, and task execution in dynamic and unstructured environments.
Features
- Sim2Real learning for realistic and adaptive gait and hand movements
- NeRF-based real-time 3D mapping and localization for navigation in complex environments
- Integration of Large Language Models for cognitive mapping and natural language understanding
- Full-body complex planning and control for end-to-end task completion from verbal command
- Agile locomotion enabling walking in any direction, running, turning, balancing, and squatting
- Fully capable hands with a full range of motion and accuracy for delicate tasks
- Automatic gait adjustment for handling varying weights