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Abstract
This paper presents a safe multi-channel communication and safety system for human-robot collaboration (HRC) in industrial applications enabled by the DiGeTac unit. This unit integrates gesture, distance, and custom-designed tactile
sensors, with gesture and distance elements on the top and the tactile element on the bottom. This design provides enhanced multimodal safety and interaction, enabling both close proximity and long-distance perception, making the
DiGeTac unit highly suitable for various collaborative scenarios. Unlike other multimodal sensors, DiGeTac offers contactless and touch-based interaction, and post- and pre-collision safety features for a broader range of tasks in HRC
environments. The performance of each sensing element within the DiGeTac unit is thoroughly evaluated through a series of validation experiments with a robot arm. The distance sensor’s accuracy is assessed in pre-collision scenarios,
ensuring reliable proximity detection for collision avoidance as part of the safety strategy. The tactile sensor is tested in a post-collision scenario, where it functions as a safety mechanism to detect impacts and trigger protective responses.
The capability of hand gestures recognition to facilitate intuitive human-robot communication is evaluated using an artificial neural network (ANN). Additionally, the tactile sensor’s contact estimation is analysed with a convolutional neural network (CNN), enhancing the robot’s ability to interact with humans and perform collaborative tasks. Finally, both safety and interaction strategies are tested in HRC scenarios, where the human operator commands the robot to move to specific positions. The results show that the DiGeTac unit is effective and has potential to improve complex collaborative tasks.
sensors, with gesture and distance elements on the top and the tactile element on the bottom. This design provides enhanced multimodal safety and interaction, enabling both close proximity and long-distance perception, making the
DiGeTac unit highly suitable for various collaborative scenarios. Unlike other multimodal sensors, DiGeTac offers contactless and touch-based interaction, and post- and pre-collision safety features for a broader range of tasks in HRC
environments. The performance of each sensing element within the DiGeTac unit is thoroughly evaluated through a series of validation experiments with a robot arm. The distance sensor’s accuracy is assessed in pre-collision scenarios,
ensuring reliable proximity detection for collision avoidance as part of the safety strategy. The tactile sensor is tested in a post-collision scenario, where it functions as a safety mechanism to detect impacts and trigger protective responses.
The capability of hand gestures recognition to facilitate intuitive human-robot communication is evaluated using an artificial neural network (ANN). Additionally, the tactile sensor’s contact estimation is analysed with a convolutional neural network (CNN), enhancing the robot’s ability to interact with humans and perform collaborative tasks. Finally, both safety and interaction strategies are tested in HRC scenarios, where the human operator commands the robot to move to specific positions. The results show that the DiGeTac unit is effective and has potential to improve complex collaborative tasks.
| Original language | English |
|---|---|
| Article number | 103109 |
| Number of pages | 23 |
| Journal | Robotics and Computer-Integrated Manufacturing |
| Volume | 97 |
| Early online date | 1 Sept 2025 |
| DOIs | |
| Publication status | E-pub ahead of print - 1 Sept 2025 |
Data Availability Statement
Data will be made available on request.Funding
This work was supported by the Republic of Türkiye Ministry of National Education and the Engineering and Physical Sciences Research Council (EPSRC) under the ‘Manufacturing in Hospital: BioMed 4.0’ project (EP/V051083/1).
| Funders | Funder number |
|---|---|
| Engineering and Physical Sciences Research Council | EP/V051083/1 |
Keywords
- Human–robot collaboration
- Multi-channel communication
- Multimodal sensing module
ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- General Mathematics
- Computer Science Applications
- Industrial and Manufacturing Engineering
Fingerprint
Dive into the research topics of 'Safe Multi-channel Communication for Human-Robot Collaboration'. Together they form a unique fingerprint.Projects
- 1 Finished
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Manufacturing in Hospital: BioMed 4.0
Leese, H. (PI), Castro Dominguez, B. (CoI), Flynn, J. (CoI), Gill, R. (CoI), Martinez Hernandez, U. (CoI), Moise, S. (CoI) & Wilson, P. (CoI)
Engineering and Physical Sciences Research Council
2/11/21 → 29/08/25
Project: Research council
