Thesis Work - Tactile-Aware Reinforcement Learning for Contact-Rich Manipulation
ABB
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 Lead Your 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:
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 to learn more about us and see the impact of our work across the globe.
R&D Center Lead Your 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.
- Period: January to July, 2027
- Number of credits: 30 ECTS/högskolepoäng (hp)
- Number of students for this thesis work: 1
- Location: on-site, Västerås
- 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
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 to learn more about us and see the impact of our work across the globe.
Den lediga tjänsten publicerades 18 dagar sedan