Name
Abstract | ||
|---|---|---|
The ability to predict, and thus react to, oncoming collisions among a set of mobile agents is a fundamental requirement for safe autonomous movement, both human and robotic. This demonstration tests a pairwise method in which two agents collect repeated range measurements and predict if they will collide. Compared to methods which use GPS or TDOA to track each agent and then predict collisions, this method does not rely on infrastructure or a fixed coordinate system. However, the accurate prediction of future pairwise range, and thus collision prediction, is highly sensitive to noise and changes in velocity. This prototype can be used to provide intuition for the method’s strengths and weaknesses. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/IPSN48710.2020.000-7 | 2020 19th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) |
Keywords | DocType | ISBN |
collision prediction,pairwise ranging,mobile agents,safe autonomous movement,range measurements,GPS,TDOA,fixed coordinate system | Conference | 978-1-7281-5498-5 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alemayehu Solomon Abrar | 1 | 11 | 3.02 |
| Neal Patwari | 2 | 3805 | 241.58 |
| Jonathan Decavel-Bueff | 3 | 0 | 0.34 |