Bachelor’s/Master’s theses in the field of quadrupedal robot systems with high load-bearing capacity

Call for applications: Master’s theses in the field of quadrupedal robot systems with high load-bearing capacity
ContactName:  Dr.-Ing. Christoph Henke (IfU) Email: christoph.henke@ifu.rwth-aachen.de Type of Thesis: Bachelor- & Masterarbeit	Source: Boston Dynamics

Quadrupedal robot systems are becoming increasingly important because they are able to operate safely even in unstructured and challenging environments where classic wheeled or tracked vehicles reach their limits. Their high mobility, stability, and adaptability open up new fields of application—for example, in industrial inspection, logistics, disaster relief, and construction.

A particular challenge lies in the development of quadrupedal systems with high payload capacity (high-payload quadrupeds). Such systems must be able to move not only their own weight but also additional payloads—such as sensors, tools, or transport goods—precisely and stably. The increased mass has a direct impact on dynamics, energy efficiency, and stability, placing high demands on control technology, drive architecture, and mechanical design.

In particular, the implementation of robust and energy-efficient gaits under heavy loads, the model-based and data-driven optimization of drive components, and safe navigation on complex terrain require deep interaction between mechatronics, robotics, and artificial intelligence.

Possible research topics:

• Machine learning-based control engineering: Development and evaluation of data-driven control approaches for implementing energy-efficient and stable gaits for quadrupedal systems with high payloads.
• Construction, design, and powertrain and joint layout of the robot system: Hardware analysis, modeling, and optimization of kinematics and overall design.
• Simulative testbed (NVIDIA Isaac Sim): Setting up a simulation environment for the development, validation, and training of ML-based methods for gait generation.
• Autonomous navigation and localization: Development and implementation of navigation strategies and localization algorithms for the quadrupedal robot in partially and unstructured environments, including obstacle avoidance.

Requirements: Interest and experience in robotics, programming (Python/C++), control engineering, and machine learning. Experience with ROS, Isaac Sim, or similar frameworks is advantageous.