Research

The TOPO lab excels in various research competencies, exercised in numerous past and ongoing projects in three general research directions.

Position and attitude determination

Position and attitude determination of moving platforms or subjects is the main-stream of the lab research activity. The laboratory expertise in algorithm development for real-time or post-mission positioning have been applied to vehicle and pedestrian navigation and trajectography. We make use of satellite based (GPS, Glonass) positioning, inertial sensors, magnetic sensors, imagery and lately the networked based positioning via Ultra-wide band or 802.x technology.

Mapping and remote sensing 

Sensor integration and close-range remote sensing competences served in development of task specific or general mobile mapping systems. Geodesy, surveying and cartography are the traditional proficiencies present in the laboratory. High precision surveying by satellite or terrestrial observations as well as network design and adjustment remains the valuable expertise that is regularly made available for consultation or research-mandates.

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Projects

Current Projects

Vehicle Dynamic Model Based Navigation

While the expansion of drone applications seems to grow without boundaries, their implementation is conditioned by operational safety. Related to that is the drone ability to maintain its intended trajectory irrespective to the disturbances in received signals through navigation autonomy. In times when drones navigation relies primary on satellite positioning (e.g. GPS), the fragility of satellite signal reception poses serious concerns in safety. Hence, there is an upswing in proposing backup plans that are mostly based on optical sensing. Nevertheless, limited visibility, resolution, or surface texture, can provide challenges for such visual based navigation systems.
 
Two parallel and complementary approaches of implementing VDM techniques are followed. The first one attempts to minimise the need of additional to classical sensor(s) (IMU, velocity measurements and control estimates). This will aim to make the approach more general rather than specific thus adopt it for low cost and existing drone configurations. The second approach is aimed for future high-end drones and EVTOL aircrafts. Having the designer freedom to incorporate in the drone design Flush Air Data System (FADS). An array of several sensors measuring states at the boundary layer of a drone. The sensor array signals are then regressed by novel physics guided machine learning algorithms in order to estimate the aerodynamic coefficients or forces directly.
 
These projects enable creation of a new technological platforms for navigation of drones that address the aspects of self-localization safety. The methodologies enable safe operation in GPS-denied environment by a novel way of using interoceptive means. This shall future proof and extend current market share in accordance with envisioned legislative evolution around the world.
 
Sponsors
 
The general development of the project is sponsored by Swiss National Science Foundation, Armasuisse, Swiss Commission for Innovation (InnoSuisse) and Swiss Data Science Centre
 

Past Projects

PEACE for UAV (Planning & Estimating Accuracy in a Cluttered Environment for UAV

This project enables precise mapping of elongated structures in inaccessible natural environment with small drones. Its implementation represents considerable savings for monitoring and management of man-made infrastructure and its protection in complex surroundings. The progress is possible through combination of state-of-the-art flying platform with advanced planning, on-line quality control of aerial vehicle position and accuracy prediction of 3D reconstruction

Real Time Quality Assessment for Airborne Lidar Mapping

The objective of this project is to put into production a small, flexible and accurate airborne mapping system that integrates laser scanner, digital imagery and navigation sensors. Unique in its size and precision it can be embarked onto a helicopter within few minutes and can provide autonomous surface mapping of an area of interest with a high precision (0.2m) and resolution (<1m²), shortly after the flying mission. Its application span from natural hazards to corridors mapping.