Thesis work -active vision for ai-based robot manipulation with a 2-dof movable camera head

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This role sits within ABB's Robotics business, a leading global robotics company. We're entering an exciting new chapter as we’ve announced the plan for SoftBank Group to acquire ABB Robotics. SoftBank is a globally recognized technology group and investor/operator focused on AI, robotics, and next-generation computing. By joining us now, you’ll be part of a pioneering team shaping the future of robotics—working alongside world-class experts in a fast-moving, innovation-driven environment.

This Position reports to: R&D Center Lead

Your role and responsibilities

In robot learning, cameras are the robot's "eyes." Most current systems use fixed cameras at static positions, which limits the field of view and the ability to observe the workspace from the best angle. A pan-tilt device is a motorized mount that can rotate the camera horizontally (pan) and vertically (tilt), giving the robot a movable "neck", similar to how humans naturally turn their head to look at objects of interest.

This thesis investigates whether equipping a robot with a 2-degree-of-freedom (2-DOF) movable camera head brings measurable benefits to AI-based robot manipulation, using a data-driven end-to-end AI approach such as Vision-Language-Action (VLA) models. This type of model takes camera images and language instructions as input and output robot actions directly.

The student will work through the full pipeline, from data collection to model deployment, supported by the ABB team at each stage. Specifically, the student is expected to:

• Extend the existing data collection software to support a movable head setup
• Upgrade the teleoperation system with neck control, enable a human operator to control the robot's neck during demonstration recording using an AR headset
• Collect demonstration data, record robot manipulation demonstrations with the movable head setup for one or more target tasks
• Train and evaluate AI models, train VLA or other suitable models that incorporate neck/head motion as part of the action space, and investigate the benefit of a movable head vs. fixed cameras
• Deploy the model on a real robot, configure the full deployment pipeline, including sending neck motion commands, handling synchronization between robot arms and head, and addressing control delays for real-time execution
• Compare the results with and without a movable camera.

The student is encouraged to propose ideas on model architecture, camera configuration (e.g., whether an additional static torso camera is needed), and evaluation strategies.

Details:

• Period: January to July, 2027
• Number of credits: 30 ECTS/högskolepoäng (hp)
• Number of students for this thesis work: One
• Location: on-site, Västerås

Qualifications for the role

• Master's student in Computer Science, Electrical Engineering, Robotics, Mechatronics, or other related fields
• Strong interest in robot learning, machine learning, computer vision, or physical AI
• Programming experience in Python and familiarity with deep learning frameworks (e.g., PyTorch, huggingface, LeRobot platform).
• Experience with git, docker, Unity, AR, etc is a plus.
• Experience with or interest in 3D data (depth images, point clouds) is a plus
• Hands-on experience with real robot systems is a plus but not required

More about us

Recruiting Manager LiWei Qi, +46 73 021 2309, Supervisor: Chi Zhang, chi.zhang@se.abb.com will answer your questions.

Positions are filled continuously. Please apply with your CV, academic transcripts, and a cover letter in English.

We look forward to receiving your application!

A Future Opportunity

Please note that this position is part of our talent pipeline and not an active job opening at this time. By applying, you express your interest in future career opportunities with ABB.

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