MULTI-AGENT PATH PLANNING OF ROBOTIC SWARMS IN AGRICULTURAL FIELDS
Creators
- 1. Robotics and Mechatronics, Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, The Netherlands
- 2. Research Centre on Interactive Media, Smart Systems and Emerging Technologies (RISE), Nicosia, Cyprus and Faculty of Electric Engineering, Mathematics and Computer Science, University of Twente, The Netherlands
- 3. Computer Science and Informatics, School of Engineering, Jönköping University, Sweden
Description
Collaborative swarms of robots/UAVs constitute a promising solution for precision agriculture and for automatizing agricultural processes. Since agricultural fields have complex topologies and different constraints, the problem of optimized path routing of these
swarms is important to be tackled. Hence, this paper deals with the problem of optimizing path routing for a swarm of ground robots
and UAVs in different popular topologies of agricultural fields. Four algorithms (Nearest Neighbour based on K-means clustering,
Christofides, Ant Colony Optimisation and Bellman-Held-Karp) are applied on various farm types commonly found around Europe.
The results indicate that the problem of path planning and the corresponding algorithm to use, are sensitive to the field topology and to the number of agents in the swarm.
Notes
Files
ISPRS2020_Multi_agent_Agri_Camera_Ready.pdf
Files
(5.8 MB)
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