Our AI & Control Team is growing to meet new challenges!

Our personal exoskeleton is evolving to operate in increasingly complex environments. To achieve this, it must be able to understand its surroundings in order to assist users with safe and robust navigation around various obstacles.

In addition, since 2025, Wandercraft has been venturing into humanoid robotics in close collaboration with the Renault Group. We are leveraging our expertise in bipedal robotics and expanding our autonomy skills for these robots. They will need to be able to locate objects of interest and estimate their poses. They will then need to understand their environment in order to navigate reliably and autonomously to fulfill our customers’ various use cases.

To this end, we are creating a team dedicated to perception and navigation. This team will be responsible for developing the knowledge and codebase needed to address these new challenges. We will explore various state-of-the-art techniques, whether based on machine learning, classical computer vision, or model-based control.

The Perception, Mapping, and Navigation team is part of the AI & Control department and works closely with other members of this department. It also collaborates regularly with other R&D teams: embedded software, electronics, and mechanics.

Your responsibilities may include:

• Selecting the most suitable vision/perception sensors for our needs

• Conducting literature reviews related to ongoing projects

• Presenting the latest innovations from the literature or internally developed algorithms to the team

• Developing algorithms for object detection, pose estimation, or feature recognition

• Creating a map of the environment that can be used to understand and navigate it

• Developing navigation and control algorithms for various robots, including autonomous navigation for humanoid robots and navigation assistance for exoskeletons

• Working closely with other teams to ensure the overall performance of the algorithms

• Testing on real robots and in simulation

• Traveling to customer sites (e.g., healthcare centers or factories) to ensure algorithms function properly in real-world conditions and making corrections as needed

• Automated testing, code quality, and designing verification pipelines to ensure non-regression

• Qualifications: Engineering degree or PhD in perception, navigation, machine learning, robotics, or a similar field.

• Experience: Ideally, you have experience in perception or navigation.

Academic experience will be valued, particularly in relation to perception or the use of point clouds, navigation or optimal control, machine learning, etc.

Creativity, innovation: you are able to develop new things with a limited existing base and to make prototypes (personal or professional robotics projects are highly appreciated).

You have an interest in experimentation and adapting algorithms to the constraints of the field and a commercial product.

You have experience in software development (Python/C++).

You have experience in team software development (modularity, responding to specifications, continuous integration, etc.).

You are comfortable with linear algebra (matrix calculations), kinematics, and physical modeling (reference frame changes, odometry, etc.).

You are rigorous, able to proofread your work and explain your calculations or algorithms clearly.

You are curious and have good analytical skills, enabling you to monitor technological developments effectively and learn from scientific literature or meetings at conferences.

Skills

• Python : expert

• C++ : expert

• Vision (feature detection, mapping, SLAM) : expert

• Navigation (path planning, path tracking…) : expert

• Machine learning (data analysis, augmentation, labeling, validation) : autonome

• Robotics (kinematics, odometry, real data analysis) : autonome

• Linear algebra, numerical optimization : autonome

• Control systems (observers, controllers) : connaissances basiques

• Continuous analysis of the state of the art in the field : autonome

• Software development best practices, continuous integration, automated testing : autonome