Sebastian Koch
Papers
3
Total Citations
17
H-Index
2
About
Sebastian Koch is an emerging researcher at the intersection of robotics, artificial intelligence, and human-robot interaction, with a particular focus on leveraging Large Language Models (LLMs) to advance autonomous robot capabilities. His most notable contribution, the **DELTA** framework (Decomposed Efficient Long-Term Robot Task Planning using Large Language Models), has garnered significant attention — accumulating 15 citations across its 2024 and 2025 iterations — and represents a meaningful step forward in enabling robots to perform complex, context-aware task and motion planning by integrating common-sense knowledge from LLMs. This work addresses longstanding challenges in long-horizon planning, pushing robots beyond rigid, pre-programmed behaviors toward more adaptive and intelligent operation. Koch has also extended his research into the domain of human behavior prediction, exploring how multimodal LLMs can anticipate human actions in shared environments — a critical capability for safe and efficient human-robot collaboration. His 2025 paper on this topic highlights both the promise and the open challenges of applying general-purpose AI models to specialized robotics contexts. With a growing citation record and contributions spanning planning, perception, and interaction, Koch represents a promising voice in next-generation intelligent robotics research.
Research Focus
Key Achievements
Top Papers
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