Register now After registration you will be able to apply for this opportunity online.
Computer Vision and Any-Angle Path Planning Algorithm for a Training App on Sprint Orienteering Maps
In this project, you will develop a tool to automatically scan and recognize obstacles in urban orienteering maps. Then, an any-angle path finding algorithm shall find the shortest route choices, which are further analyzed in terms of elevation gain, running speed and amount of turns.
Keywords: Graph Theory, Computer Vision, Pathfinding, Orienteering, Sport
In urban orienteering races, athletes must find the fastest route on their map in split seconds under a high physical stress.
This skill can be trained with various methods, one of them being in a digital form in front of a screen.
However, preparation of such training is a time-intensive task for the coaches.
An automatic tool to recognize the standardized symbols and obstacles on an urban orienteering map and a path finding algorithm can reduce the required workload by a lot.
In this project, you will first compare and implement computer vision algorithms to recognize urban orienteering maps.
In a second step, you will evaluate and implement a path planning strategy to find the euclidean shortest route(s) between any two given control points on the map.
The fastest routes shall be further classified in terms of elevation gain, number of change of direction and terrain.
In urban orienteering races, athletes must find the fastest route on their map in split seconds under a high physical stress. This skill can be trained with various methods, one of them being in a digital form in front of a screen. However, preparation of such training is a time-intensive task for the coaches. An automatic tool to recognize the standardized symbols and obstacles on an urban orienteering map and a path finding algorithm can reduce the required workload by a lot.
In this project, you will first compare and implement computer vision algorithms to recognize urban orienteering maps. In a second step, you will evaluate and implement a path planning strategy to find the euclidean shortest route(s) between any two given control points on the map. The fastest routes shall be further classified in terms of elevation gain, number of change of direction and terrain.
beglinger@hpe.ee.ethz.ch
beglinger@hpe.ee.ethz.ch
30% Computer Vision
30% Pathfinding
20% User Interface
20% Backend
30% Computer Vision 30% Pathfinding 20% User Interface 20% Backend