| 1. |
- Wang, Lihui, et al.
(författare)
-
Overview of Human-Robot Collaboration in Manufacturing
- 2020
-
Ingår i: Proceedings of 5th International Conference on the Industry 4.0 Model for Advanced Manufacturing. - Cham : Springer. ; , s. 15-58
-
Konferensbidrag (refereegranskat)abstract
- Human-robot collaboration (HRC) in the manufacturing context aims to realise a shared workspace where humans can work side by side with robots in close proximity. In human-robot collaborative manufacturing, robots are required to adapt to human behaviours by dynamically changing their pre-planned tasks. However, the robots used today controlled by rigid native codes can no longer support effective human-robot collaboration. To address such challenges, programming-free and multimodal communication and control methods have been actively explored to facilitate the robust human-robot collaborative manufacturing. They can be applied as the solutions to the needs of the increased flexibility and adaptability, as well as higher effort on the conventional (re)programing of robots. These high-level multimodal commands include gesture and posture recognition, voice processing and sensorless haptic interaction for intuitive HRC in local and remote collaboration. Within the context, this paper presents an overview of HRC in manufacturing. Future research directions are also highlighted.
|
|
| 2. |
- Liu, Sichao, et al.
(författare)
-
A Framework of Data-Driven Dynamic Optimisation for Smart Production Logistics
- 2020
-
Ingår i: APMS 2020: Advances in Production Management Systems. Towards Smart and Digital Manufacturing. - Cham : Springer. ; , s. 213-221
-
Konferensbidrag (refereegranskat)abstract
- Production logistics systems in the context of manufacturing, especially in automotive sectors today, are challenged by the lack of real-time data of logistics resources, optimal configuration and management strategies of materials, and optimisation approaches of logistics operations. This turns out to be the bottleneck in achieving flexible and adaptive logistics operations. To address these challenges, this paper presents a framework of real-time data-driven dynamic optimisation schemes for production logistics systems using the combined strength of advanced technologies and decision-making algorithms. Within the context, a real-time data sensing model is developed for the timely acquisition, storage, distribution, and utilisation of equipment and process data in which sensing devices are deployed on physical shop floors. The value-added data enable production logistics processes to be digitally visible and are shared among logistics resources. A multi-agent-based optimisation scheme for production logistics systems based on real-time data is developed to obtain the optimal configuration of logistics resources. Finally, a prototype-based simulation within an automotive manufacturing shop floor is used to demonstrate the proposed conceptual framework.
|
|
| 3. |
|
|
| 4. |
- Liu, Sichao, et al.
(författare)
-
Symbiotic human-robot collaboration : Multimodal control using function blocks
- 2020
-
Ingår i: Procedia CIRP. - : Elsevier B.V.. - 2212-8271. ; , s. 1188-1193
-
Konferensbidrag (refereegranskat)abstract
- Complex assembly tasks require increased flexibility and adaptability, as well as higher effort on the conventional (re)programming of robots. To solve such challenges, this paper presents a function block-enabled multimodal control scheme for symbiotic human-robot collaborative assembly. Data/event-driven function blocks with smart decision algorithms are used for human-centred robot control with multimodal fusion. Then, multimodal control commands in the form of haptics, gesture and voice are defined as the inputs of the function blocks to trigger task execution. This novel scheme facilitates the implementation of the multimodal symbiotic human-robot collaborative assembly with enhanced stability and flexibility.
|
|
