2024–2027
Project Duration
ERDF
EU Funding
4
Research Focus Areas
21
Publications
64
Citations
ERDF research project
ENABLING
Resilient Human-Robot Collaboration in Mixed-Skill Environments
ENABLING
ENABLING (Resilient Human-Robot Collaboration in Mixed-Skill Environments) addresses the problem area of developing AI methods to complement the skills of robots and humans. It thus enables research innovations in cross-sectional areas of IT and key enabling technologies and forms the basis for future applications in the lead markets. The challenges lie, firstly, at the interface between robotics and AI and, secondly, in the complexity of tasks in a mixed-skill environment and, thirdly, in resilient and responsible collaboration. These are to be achieved by developing the key technologies for 1. robust recording of the affective user state, 2. semantic environment analysis, 3. intention-based interpretation of user actions, 4. and research into generative models for recording complex behavior in mixed-skill environments.
The project is funded by the European Regional Development Fund (ERDF) under grant No. ZS/2023/12/182056 and is planned with a project duration of 4 years (2024 to 2027).
Breakthrough Innovations
01
AI-Based User Perception
Robust AI perception of users in mixed-skill scenarios with occlusion, dynamic environments, and divided attention.
02
Social Signal Interpretation
Distinguishing task-directed actions, social interactions, and incidental movements from user signals and affective states.
03
Semantic Environment Analysis
Recognising user actions in spatial context — enabling intentional, anticipatory systems aware of environment and intent.
04
Affective State Detection
Real-time detection of user affect via gestures, facial expressions, and vital signs for non-verbal feedback and alignment.
05
Generative Behaviour Models
Generative AI models unifying multi-modal prediction to build comprehensive situation models of complex user behaviour.
Latest News
Vision on the Warehouse Floor: Perceptive HRI for Autonomous Forklifts
September 30, 2026
We present an integrated vision system for autonomous forklifts that combines RGB-only 6D pallet pose estimation with gesture- and face-based...
See, Spawn, Synchronize: A Digital Twin Pipeline for Smart Production Cells
August 28, 2026
We present a digital twin of a smart production cell that synchronizes objects bidirectionally between a real and a virtual...
REMA-Net: Real-Time Human Action Recognition via Caption-Guided Dual-Stream Attention
August 26, 2026
REMA-Net is a lightweight dual-stream framework for real-time human action recognition that pairs RGB visual features with semantic embeddings derived...
SAR-SLAM: Semantic-Aware Recognition for Dynamic SLAM in Robotic Applications
July 20, 2026
SAR-SLAM is an RGB-D SLAM framework that keeps tracking reliable when people and objects move through the scene. It combines...
Intent Recognition in Speech-to-Text Processing in the Context of Natural Interaction with Cognitive Assistive Systems
May 11, 2026
This study investigates efficient speech-to-intent recognition for human–robot interaction in elderly-care environments in German, targeting deployment on resource-constrained platforms such...
GESTRO: Skeleton-Based Dynamic Gesture Recognition for Robot Teleoperation
April 16, 2026
We introduce GESTRO, a dataset of 11 dynamic gestures for the intuitive teleoperation of mobile robots, comprising 3,300 samples recorded...