As technology advances, robotic agents are being applied to more areas. Consequently, their environments are becoming more complex, moving away from the standard - mainly static - work cells, where operators and machines follow strictly defined boundaries and schedules. The non-deterministic workflow of these workspaces raises concerns about planning tasks and actions between resources. The traditional approach to human-robot interfaces is based on explicit programming and pre-defined commands. However, with AI and natural language processing advances, incorporating semantic knowledge into the interfaces may enable more natural, intuitive and context-aware interactions between humans and robots. Semantic knowledge and ontologies enable the interface to understand the context of the task planning process. This understanding allows robotic agents to consider the overall situation, the environment and any relevant previous tasks or actions, resulting in more context-appropriate task execution. Following these requirements, this paper presents a graphical user interface which uses semantic knowledge to assist an operator human in task planning for robotic agents, minimising human error.
The Use of Semantic Knowledge in Task Planning for Robotic Agents, Minimising Human Error
Lect. Notes in Networks, Syst.
Iberian Robotics conference ; 2023 ; Coimbra, Portugal November 22, 2023 - November 24, 2023
2024-04-27
11 pages
Article/Chapter (Book)
Electronic Resource
English
Minimising the potential for human error in ship operation
British Library Conference Proceedings | 1995
|Robotic task planning: independent of agents but dependent on time
Tema Archive | 1989
|Useful Interactions Between Human and Robotic Agents Performing a Cooperative Assembly Task
British Library Conference Proceedings | 2003
|Engineering Index Backfile | 1939