M2 Room

Human-Machine Interface

M2 focuses on the dynamics of remote human–machine interaction and robust approaches for interfaces, aiming to improve anticipatory capabilities and situational awareness for more effective interactions.

Key Questions

We will develop multimodal models to improve prediction even under visual occlusion.

We will explore multimodal visualizations to promote transparency and trust, enabling transitions between human and autonomous control.

We will study digital twins and feedback strategies to improve physical interaction at a distance.

We will study semantic representations to synthesize haptic feedback.

We will analyze how social cues affect trust, considering various contexts.

Approach

  • Human Activity Understanding and Intent Prediction: Using models from M1, we will extract contextual and gestural information, with applications for assistive systems (U2).
  • Shared Autonomy: We will develop a shared autonomy framework for robotics and teleoperation, applied in surgery (U1).
  • HMI Design for Remote Physical Interaction: Define design requirements using digital twins and sensors.
  • Semantic Communication of Haptic Signals: Develop models to reduce bandwidth consumption and enhance haptic synthesis.
  • Social Touch and Trust: Investigate the impact of social cues on trust. 

Expected Results

  • 10% improvement in intent prediction accuracy.
  • 30% reduction in data rate with semantic models.
  • Shared autonomy framework tested with U5.

Our Latest Research Results

  • The Psychology of Trust in High-Risk AI Systems

    As Artificial Intelligence systems rapidly transition from passive tools to active teammates in healthcare, workplaces, and education, a critical question emerges: Is it enough for a system to be rel ...

  • The Illusion of Certainty – Why We Over-Trust Our Sense of Touch

    We often believe that seeing is believing—but when it comes to true certainty, we tend to rely even more on what we can physically feel. A special new study from the ConTakt Lab at TU Dresden dives i ...

  • Designing the Perfect Touch – How Soft Actuators Meet Human Perception

    Can a glove integrated with liquid dielectric actuators change the way we interact with virtual worlds? A new collaborative study explores exactly that—building a crucial bridge between soft robotics ...

  • Charting the Challenges and Opportunities of Mixed Presence in Mixed Reality

    Developing environments where physical and virtual users can seamlessly interact is incredibly complex. At this year's ACM CHI Conference on Human Factors in Computing Systems (CHI 2026) in Barcelona ...