Enhanced STag Marker System: Materials and Methods for Flexible Robot Localisation
Accurate localisation is key for the autonomy of mobile robots. Fiducial localisation utilises relative positions of markers physically deployed across an environment to determine a localisation estimate for a robot. Fiducial markers are strictly designed, with very limited flexibility in appearance. This often results in a “trade-off” between visual customisation, library size, and occlusion resilience. Many fiducial localisation approaches vary in their position estimation over time, leading to instability. The Stable Fiducial Marker System (STag) was designed to address this limitation with the use of a two-stage homography detection. Through its combined square and circle detection phases, it can refine detection stability. In this work, we explore the utility of STag as a basis for a stable mobile robot localisation system. Key marker restrictions are addressed in this work through contributions of three new chromatic STag marker types. The hue/greyscale STag marker set addresses constraints in customisability, the high-capacity STag marker set addresses limitations in library size, and the high-occlusion STag marker set improves resilience to occlusions. These are designed with compatibility with the STag detection system, requiring only preprocessing steps for enhanced detection. They are assessed against the existing STag markers and each shows clear improvements. Further, we explore the viability of various materials for marker fabrication, for use in outdoor and low-light conditions. This includes the exploration of “active” materials which induce effects such as retro-reflectance and photo-luminescence. Detection rates are experimentally assessed across lighting conditions, with “active” markers assessed on the practicality of their effects. To encapsulate this work, we have developed a full end-to-end deployment for fiducial localisation under the STag system. It is shown to function for both on-board and off-board localisation, with deployment in practical robot trials. As a part of this contribution, the associated software for marker set generation/detection, physical marker fabrication, and end-to-end localisation has been released as an open source distribution.
Funding
EPSRC Centre for Doctoral Training in Agri-Food Robotics: AgriFoRwArdS
Engineering and Physical Sciences Research Council
Find out more...History
School affiliated with
- Lincoln Institute for Agri-Food Technology (Research Outputs)
- School of Computer Science (Research Outputs)
- College of Health and Science (Research Outputs)
Publication Title
MachinesVolume
13Issue
1Pages/Article Number
2Publisher
MDPIExternal DOI
eISSN
2075-1702Date Submitted
2024-11-09Date Accepted
2024-12-17Date of First Publication
2024-12-24Date of Final Publication
2024-12-24Open Access Status
- Open Access
Will your conference paper be published in proceedings?
- N/A