Thesis Work - Tactile-Aware Reinforcement Learning for Contact-Rich Manipulation
At a glance
Mid-level AI Research role at Abb. Vaesteras.
Pay not stated AI Research salary
aimlroles summary, based on the employer's posting.
What you'll do
- Review research on tactile sensing, dexterous manipulation, and robot learning using Isaac Sim and Isaac Lab
- Add tactile sensing to the provided robot-hand simulation using contact data from Isaac Sim
- Build reinforcement learning environments and train policies for grasping, object handling, pick-and-place, or insertion
- Compare tactile-based policies with proprioception-only baselines, measuring success, robustness, and sim-to-real transfer
What you bring
- You are a master's student interested in robotics and reinforcement learning
- You understand robotics fundamentals such as kinematics, dynamics, and control, along with machine learning basics
- You can work with Linux and Git
Who this fits
This thesis suits a master's student looking to develop and evaluate tactile-guided manipulation methods, with room to explore ideas in tactile representations, learning, tasks, or sim-to-real transfer. It runs from January to July 2027, is worth 30 ECTS, and is based on-site in Västerås. Python, C++, and ROS 2 experience is preferred.
From the employer
At ABB, we help industries outrun - leaner and cleaner. Here, progress is an expectation - for you, your team, and the world. As a global market leader, we’ll give you what you need to make it happen. It won’t always be easy, growing takes grit. But at ABB, you’ll never run alone. Run what runs the world.
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 LeadYour role and responsibilities
This thesis combines both investigation and prototype development in the area of tactile-guided robotic manipulation. The student will investigate how tactile sensing can improve the performance and robustness of contact-rich manipulation tasks. A digital twin of a robot arm equipped with a Psyonic/Linkerbot Hand will be provided by the supervisors in NVIDIA Isaac Sim. Building on this foundation, the student will extend the simulation framework with tactile sensing capabilities, develop reinforcement learning training environments and pipelines in NVIDIA Isaac Lab, and evaluate tactile-guided manipulation policies in simulation, with optional validation on real hardware.
The work is expected to include:
- Conducting a literature review on tactile sensing, dexterous manipulation, and robot learning methods on Isaac Sim & Isaac Lab.
- Developing tactile sensing simulation based on contact information available in Isaac Sim.
- Implementing and training reinforcement learning policies for contact-rich manipulation tasks such as grasp stabilization, object manipulation, pick-and-place, and insertion.
- Comparing tactile-aware policies against proprioception-only baselines.
- Evaluating policy performance in terms of task success rate, robustness, and sim-to-real transfer capability.
The project has a well-defined technical direction, but students are encouraged to propose and explore their own ideas regarding tactile representations, learning algorithms, task design, or sim-to-real transfer strategies. We are open to suggestions that align with the overall goal of improving tactile-guided robotic manipulation.
Details:
- Period: January to July, 2027
- Number of credits: 30 ECTS/högskolepoäng (hp)
- Number of students for this thesis work: 1
- Location: on-site, Västerås
The thesis will be jointly supervised by two supervisors with complementary expertise in robotics and AI. Students will receive guidance on simulation development and tactile sensing, as well as on robot learning methods such as reinforcement learning and imitation learning. Additional expertise in robotics and control systems will be available throughout the project, providing comprehensive support across both AI and robotics domains.
Qualifications for the role
- Master students interested in robotics and reinforcement learning
- Python, C++, ROS 2 experience is preferred
- Robotics fundamentals (kinematics, dynamics, control)
- Machine learning basics
- Linux and Git
More about us
Recruiting Manager LiWei Qi, +46 73 021 2309, Supervisors: Tong Hui, tong.hui@se.abb.com Zhen Li zhen.li@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.
We value people from different backgrounds. Could this be your story? Apply today or visit www.abb.com to learn more about us and see the impact of our work across the globe.
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