---
title: "Closing the Motion Execution Gap: From Semantic Motion Task Constraints to Kinematic Control"
authors:
  - "Simon Stelter"
  - "Vanessa Hassouna"
  - "Malte Huerkamp"
  - "Michael Beetz"
doi: "10.24963/ijcai.2026/845"
url: "https://ijcai.org/proceedings/2026/845"
pdf: "https://ijcai.org/proceedings/2026/0845.pdf"
venue: "Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence"
year: 2026
pages: "7601-7609"
track: "AI and Robotics"
keywords:
  - "Structured, semantic, and explicit world models, digital twins, and action representations: Explicit action representations such as task schemas, scripts, and parameterized skills"
  - "Robot control, planning, and execution with guarantees: Online monitoring, explanation, and adaptation"
  - "Structured, semantic, and explicit world models, digital twins, and action representations: Structured world models and semantic digital twins"
  - "Robot control, planning, and execution with guarantees: Architectures connecting high-level intent and constraints to low-level trajectories"
---

# Closing the Motion Execution Gap: From Semantic Motion Task Constraints to Kinematic Control

Simon Stelter, Vanessa Hassouna, Malte Huerkamp, Michael Beetz

*Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence*, pages 7601-7609. DOI: [10.24963/ijcai.2026/845](https://doi.org/10.24963/ijcai.2026/845)

## Abstract

This paper addresses the Motion Execution Gap, the disconnect between high-level symbolic task descriptions using semantic constraints and executable robot motions.
\textbf{Motion Statecharts} are introduced as an executable symbolic representation for complex motions.
They allow the arbitrary arrangement of motion constraints, monitors or nested statecharts in parallel and sequence.
World-centric motion specification and generalization across embodiments are enabled through the use of a unified differentiable kinematic world model of both, robots and environments.
Motion execution is realized through a \ac{lmpc}-based implementation of the task-function approach, in which smooth transitions during task switches are ensured using jerk bounds.
Cross-platform transferability was demonstrated by deploying the method on eight robot platforms, operating in diverse environments.
The proposed framework is called Giskard and is available open source (https://github.com/cram2/cognitive_robot_abstract_machine).