About us:

In a world where artificial intelligence opens up new horizons, our faith in its potential unveils a new outlook where, together, humans and machines build a new future filled with knowledge, inspiration, and incredible discoveries.

The development of a functional humanoid robot underpins an era of abundance and well-being where poverty will disappear, and people will be able to choose what they want to do.

We can imagine millions of bipedal robots doing more work than all human labour does today freeing people from the servitude of some repetitive and boring tasks that nobody likes to perform.

We believe that we have enough abundance to take care of everyone who is displaced. Eventually, providing a universal basic income will lead to the true evolution of our civilization.

Labor shortages loom, as the demands on our built environment rise. With the world’s workforce increasingly moving away from undesirable tasks, the manufacturing, construction, and logistics industries critical to our daily lives are left exposed.

By deploying our general-purpose humanoid robots in environments deemed hazardous or monotonous, we envision a future where human well-being is safeguarded while closing the gaps in critical global labour needs.

Responsibilities

• SLAM Algorithm Development: Design, implement, and optimize SLAM algorithms and techniques for real-time localization and mapping of robotic systems, including feature-based, visual, and LiDAR-based SLAM methods.
• Sensor Fusion: Integrate data from multiple sensors such as cameras, LiDAR, IMUs, and odometry to improve the accuracy and robustness of SLAM algorithms, and develop sensor fusion techniques for accurate pose estimation and mapping.
• Localization and Mapping: Develop algorithms for accurate localization of robotic platforms within their environment, and generation of 2D or 3D maps of the environment, using SLAM techniques such as graph-based optimization and probabilistic filtering.
• Calibration and Sensor Characterization: Perform calibration and characterization of sensors used in SLAM systems, including intrinsic and extrinsic calibration of cameras and LiDAR sensors, to ensure accurate sensor measurements and data fusion.
• Performance Optimization: Optimize SLAM algorithms for computational efficiency, memory usage, and real-time performance on embedded hardware platforms, to enable deployment in resource-constrained robotic systems.
• Robotic Navigation: Collaborate with robotics and control engineers to integrate SLAM algorithms into navigation and control systems of robotic platforms, and develop navigation algorithms for autonomous exploration and path planning.
• Evaluation and Validation: Conduct evaluation and validation of SLAM algorithms and systems through simulation and real-world testing, and analyze performance metrics such as localization accuracy, map quality, and computational efficiency.
• Research and Innovation: Stay updated with the latest research and developments in SLAM algorithms, sensor technologies, and robotics, and contribute to research projects and publications in the field of robotic mapping and localization.

Expertise

• Strong theoretical and practical knowledge of SLAM algorithms and techniques, including feature-based SLAM (e.g., ORB-SLAM), visual SLAM (e.g., SVO), and LiDAR SLAM (e.g., LOAM), and ability to implement and customize SLAM algorithms for specific robotic applications.