Maximilian Xiling Li

Maximilian Xiling Li

PhD Researcher · Intuitive Robots Lab

Karlsruhe Institute of Technology

PhD researcher at the Intuitive Robots Lab, Karlsruhe Institute of Technology, advised by Rudolf Lioutikov. I work on concept-aware robot policies: making manipulation more robust by grounding learned policies in high-level concepts like visual affordances and force awareness, an idea rooted in my interest in explainable AI.

Research

My research asks how robots can extract richer information from available data rather than simply requiring more of it. Starting from an interest in explainable AI, making the decisions of learned models transparent and interpretable, I arrived at the idea that grounding policies in human-understandable concepts can also make them more robust. Under the theme of Concept-Aware Robot Policies (CARP), I investigate how underutilized concepts such as visual affordances, and force-aware action representations, can be integrated into learned policies to improve manipulation performance.

Robot Learning Visual Affordances Movement Primitives Force-Aware Control Imitation Learning Explainable AI Robot Manipulation

Background

Max studied Computer Science at TU Darmstadt, during which he also worked as a research working student at SAP in Big Data Intelligence and Research (2013–2017). During his bachelor's he was an exchange student at Tongji University in Shanghai. He continued at KIT for his master's, working as a research assistant at the Human-Centered Systems Lab and the Autonomous Learning Robots Lab, before joining the Intuitive Robots Lab as a PhD researcher in 2022.

Selected Publications

Multi-Objective Photoreal Simulation (MOPS) Dataset for Computer Vision in Robotic Manipulation Maximilian Xiling Li, Paul Mattes, Nils Blank, Korbinian Franz Rudolf, Paul Werner Lödige, Rudolf Lioutikov Workshop on Structured World Models for Robotic Manipulation, 2025
Use the Force, Bot! — Force-aware ProDMP with Event-based Replanning Paul Werner Lödige, Maximilian Xiling Li, Rudolf Lioutikov ICRAIEEE International Conference on Robotics and Automation, 2025
Information Maximizing Curriculum: A Curriculum-based Approach for Learning Versatile Skills Denis Blessing, Onur Celik, Xiaogang Jia, Moritz Reuss, Maximilian Li, Rudolf Lioutikov, Gerhard Neumann NeurIPSAdvances in Neural Information Processing Systems, 2023
Goal Conditioned Imitation Learning using Score-based Diffusion Policies Moritz Reuss, Maximilian Li, Xiaogang Jia, Rudolf Lioutikov RSSRobotics: Science and Systems, 2023

View all publications →