Recorded live at the European Robotics Forum 2026 in Stavanger, this special episode of Among Us: Human–Robot Teaming takes you inside one of Europe’s most important robotics gatherings—through conversations, demos, and cutting-edge research.

This is not theory. This is what robotics actually looks like today.

We start with Nabil Belbachir, organizer of ERF, discussing:

1. The strategic direction of robotics in Europe
2. Where industry and research are actually converging
3. Why events like ERF matter beyond networking

Next, a fascinating discussion with Matěj Karásek from Flapper Drones:

1. How flapping-wing drones differ from traditional UAVs
2. The role of bio-inspired design in robotics
3. Real-world applications where conventional drones fail

We then speak with Marco Aggravi, Project Manager and R&D Engineer at Haption:

1. High-fidelity force feedback systems
2. The role of haptics in teleoperation and training
3. Why touch is still the missing piece in many robotic systems

A hands-on demo with SenseGlove showcases:

1. Real-time haptic feedback in virtual and robotic environments
2. Applications in training, simulation, and remote manipulation
3. The transition from demo tech → deployable systems

The episode concludes with a presentation of the paper:

“Transformer-Based Human Trajectory Prediction in Manufacturing Settings”

Authored by:

1. Even Langås
2. Atle Aalerud
3. Daniel Hagen
4. Filippo Sanfilippo

Key ideas explored:

1. Predicting human motion in industrial environments
2. Using transformer architectures for temporal modeling
3. Improving safety and fluency in human–robot collaboration

At first glance, these look like separate topics:

1. Event organization
2. Bio-inspired drones
3. Haptics
4. Wearable interfaces
5. AI-based trajectory prediction

They’re not.

They all point toward one thing:

👉 Robots that understand, adapt, and physically interact with humans in real environments

Most robotics systems today:

1. Perceive poorly
2. Predict weakly
3. Interact unnaturally

This episode shows what it takes to fix that:

1. Better sensing (event cameras, multimodal systems)
2. Better prediction (transformers, temporal models)
3. Better interaction (haptics, wearable feedback)

1. Robotics researchers and PhD students
2. Engineers working on HRI/HRC systems
3. Anyone serious about moving from demos → deployable systems

If you want real human–robot teaming, you need to combine:

1. Perception + Prediction + Physical Interaction

Miss one—and your system breaks in the real world.

Join us in this episode as we explore the cutting-edge developments in human-robot collaboration, emphasizing sensor technologies, gesture-based interfaces, privacy preservation, and emotional understanding. Hamza Zafar shares insights from his PhD research, highlighting how new sensors and algorithms are transforming the way humans and robots work together safely and intuitively.

Main Topics Covered:

1. The evolution and impact of gesture-based interfaces in human-robot teaming
2. The role of neuromorphic event cameras versus traditional RGB cameras
3. Privacy-preserving techniques such as federated learning in sensor data
4. Integration of digital twins and Industry 5.0 for dynamic, human-centric environments
5. Predicting human intentions and emotional states to enhance collaboration
6. Future perspectives: robots cohabiting living spaces, especially aiding elderly people

Timestamps:

00:00 - Introduction to "Among Us" podcast and episode theme

01:23 - High-level overview of human-robot teaming and core elements

04:16 - Hamza discusses gesture-based interfaces and sensor types

05:36 - Sensors used in human-robot interaction: RGB, EMG, neuromorphic cameras

07:18 - Privacy-preserving methods in gesture recognition using federated learning

09:09 - Differences between traditional and predictive gesture interfaces

10:54 - Real-time limb and hand tracking for improved robot responsiveness

13:40 - Merging digital twins with machine learning for Industry 5.0

16:17 - Ensuring safety and risk mitigation via digital twins

17:25 - Future visions: robots living with humans, especially the elderly

20:50 - Incorporating emotion prediction and physiological sensing

23:33 - Physiological vs non-verbal emotion recognition for adaptive systems

26:27 - The importance of interdisciplinary collaboration in advancing HRT

28:24 - Neuromorphic event cameras: how they work and their advantages

32:49 - Summary of benefits of event cameras: efficiency, privacy, low data load

34:17 - Final thoughts, collaborations, and closing remarks

Resources & Links:

1. Hamza Zafar's Scholar Profile
2. Exploring the synergies between collaborative robotics, digital twins, augmentation, and industry 5.0 for smart manufacturing: A state-of-the-art review
3. Empowering Human-Robot Interaction Using sEMG Sensor: Hybrid Deep Learning Model for Accurate Hand Gesture Recognition
4. Federated learning-enhanced edge deep learning model for EMG-based gesture recognition in real-time human–robot interaction
5. Harmony unleashed: Exploring the ethical and philosophical aspects of machine learning in human-robot collaboration for industry 5.0

Connect with Hamza:

1. LinkedIn

In this episode, we bridge the latest technological advancements with the ethical and human-centered considerations essential for safe and effective human-robot collaboration.

In this episode, we explore the evolving field of human-robot teaming (HRT), emphasizing the importance of understanding human psychology, nonverbal communication, and ethical considerations in creating trustworthy and effective robotic partners. Our guest, Dr. Cristina Brasi, brings her expertise in forensic psychology and behavioral analysis to shed light on how robots can better read and respond to human cues, especially in high-pressure environments.

Key Topics

1. The evolution of human-robot interaction from isolated robots to collaborative teams
2. The role of sensors, actuators, and algorithms in enabling effective teaming
3. The importance of personalized behavioral calibration over universal models
4. Recognizing behavioral leakage and micro-expressions to interpret true emotions
5. Cognitive ergonomics: tailoring robotic communication to individual neural profiles
6. Challenges and risks of robot misinterpretation in emergency and stressful scenarios
7. Designing transparent and predictable robots to foster trust
8. The ethical implications of robots analyzing micro-expressions and emotional states
9. The vision of a future where robots recognize and respect the complex social fabric of human life
10. Bridging the "invisible barrier" and liberating both humans and machines for more harmonious coexistence

Timestamps

00:00 - Introduction to human-robot teaming and its significance

03:08 - Why robots need to move beyond mere automation and towards true collaboration

04:32 - The evolution from industrial robots to physical and shared space teaming

05:29 - Critical elements for effective human-robot interaction: sensors, actuators, algorithms

06:56 - The importance of humanizing robots through emotional and behavioral understanding

12:21 - The story behind naming the robot "Ambroggio" and symbolic meaning

13:43 - Identifying gaps between robotics and behavioral sciences

14:12 - Personalizing robotic responses through behavioral signatures and leakage detection

15:11 - Moving from action recognition to intent recognition in robots

16:08 - Embracing cognitive ergonomics and adapting to diverse neural profiles

18:28 - Risks of misinterpreting signals in emergency rescue environments

19:38 - Distinguishing pain vs. deception through micro-dynamic gesture analysis

20:35 - The importance of social fluency and subtle cues in high-stakes scenarios

22:27 - Defining successful human-robot non-verbal collaboration: trust, transparency, predictability

24:20 - Designing robots that display their internal states visually for better predictability

27:35 - The future potential of human-robot teaming in mental health and operational safety

29:14 - Contextual adaptive responses for social appropriateness

30:12 - The vision of robots recognizing and respecting the social fabric of human life

31:50 - Closing remarks and encouragement for ongoing collaboration

Resources & Links

1. Emotion recognition with a Randomized CNN-multihead-attention hybrid model optimized by evolutionary intelligence algorithm

Connect with Dr. Cristina Brasi:

1. LinkedIn

Join us in future episodes as we continue to unravel the fascinating intersection of human psychology, AI, and robotics. Stay tuned for more inspiring insights and innovative visions for a harmonious future of humans and robots working together.