AI-Driven Autonomy for Ground and Aerial Robotic Systems
Indexed description
The candidate will address challenges across diverse application domains such as agriculture, logistics, construction, search and rescue, inspection and maintenance, healthcare, and advanced manufacturing, focusing on integrating Artificial Intelligence into real-world robotic systems to increase autonomy, adaptability, and cognitive capabilities.
We are looking for candidates with strong robotics software development skills (including ROS/ROS2) and proven experience working with real robotic platforms and field deployments.
Our group specializes in applied research and development in service and industrial robotics, aiming to enhance robot intelligence for complex behaviours in real environments. We focus on:
- Ground and Aerial robot’s autonomous navigation.
- Perception, cognition, and behaviour modelling.
- Fleet coordination and cooperative multi-robot systems.
- Human-robot collaboration and AI-driven decision-making.
RESPONSIBILITIES:
- Participate in the definition, design, and development of new AI-driven robotics concepts.
- Scientific and technical contributions to project advancements.
- Development, validation, and maintenance of high-quality software for applied research in robotics.
- Integration and deployment of robotic systems in field trials.
- Participation in scientific publications and dissemination activities.
- Support project management to ensure proper execution and delivery.
- Maintain active collaboration with clients, partners, and multidisciplinary teams.
Required Skills
Academic Background
- PhD, MSc, or equivalent experience in Robotics, AI, Computer Vision, or related fields.
- Strong background in autonomous navigation and localization, including path planning, SLAM, and perception systems for ground and/or aerial platforms.
- Proficiency in ROS/ROS2 and solid programming skills (C++ and Python)
- Familiarity with simulation environments for mobile robotics (e.g., Gazebo, AirSim, or Isaac Sim).
- AI/ML applied to robotics (semantic mapping, 3D scene understanding, reinforcement learning, or multi-robot coordination).
- Experience with Edge AI deployment: optimizing Deep Learning models for real-time execution on onboard hardware (Jetson, NUC).
- Experience with real robotic platforms.
- Experience in the design and implementation of advanced control architectures for multirotor and VTOL (Vertical Take-Off and Landing) platforms.
- Experience with low-level control for aerial robots.
- Knowledge of flight control stacks such as PX4 or ArduPilot, and their integration with ROS/ROS2 (Mavros/DDS).
- Experience in the implementation of multi-agent coordination strategies for heterogeneous fleets (UAVs and UGVs) in collaborative tasks.
- Fleet-level optimization.
- Advanced 3D perception (LiDAR, RGB-D, stereo) and scene understanding.
- Semantic mapping and world modeling for long-horizon autonomy.
- Behaviour planning and decision-making architectures.
- Integration of learning-based components into navigation stacks.
- Excellent communication skills, adaptability, and creativity.
- Fluent English; other languages are a plus.
- Availability to travel occasionally.
Additionally, we offer:
- Permanent contract.
- Hybrid work model (home office/office).
- Flexible working hours, shorter workdays on Fridays, and summer schedules.
- Flexible remuneration package (health insurance, transport, lunch, studies/training, and kindergarten).
- Professional growth through Eurecat Academy courses, weekly thematic sessions on Eurecat’s areas of knowledge, and language training (English, Catalan, Spanish).
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