Research projects

Augmented Reality environments will be used, as they naturally allow for situated interaction and visualizations, such as error-tree visualization. With respect to measurement tools, the goal is to simplify the learning curve for measurement products, such that forepersons and supervisors can interface them with limited experience with surveying equipment. Furthermore, it is ultimate to keep up-to-date with trends in automation for easing user-adoption of products. A high accuracy of the measurements and interaction paradigms with low-latency are important to facilitate user adoption.

• Develop effective visualizations to support the understanding of errors in complex systems. We will make use of 3D registered and context-aware visualizations using Augmented Reality, with a focus on error-trees and root cause analysis.
• Develop natural user interaction techniques to interact with the described analysis system.
• Design, implement and improve the single source of truth (SSOT) paradigm to avoid error-prone data redundancy and to ensure consistency by construction.
• Define, implement and evaluate training processes in collaboration with the AVL SkillsCenter. The resulting prototype should enable non-expert users to author a training scenario on the fly.
• Investigate active localization, which pertains to optimizing an agent’s decision process while interacting with an environment, in order to reach a desired goal state.
• Develop suitable algorithms for indoor and outdoor usage.
• Develop methodologies for choosing an optimal sampling of the scene to ultimately provide an accurate position and orientation estimate for an agent.
• Evaluate further appliances and use-cases to provide design and decision guidelines for future development.