| dc.contributor | Munguia, R., Departament of Computer Science, CUCEI, Universidad de Guadalajara, Mexico; Manecy, A., Control Systems Department, GIPSA-Lab, Grenoble and ISM (Institute of Movement Science), Marseille, France | |
| dc.creator | Munguia, R. | |
| dc.creator | Manecy, A. | |
| dc.date.accessioned | 2015-11-19T18:57:33Z | |
| dc.date.accessioned | 2022-11-02T17:01:48Z | |
| dc.date.available | 2015-11-19T18:57:33Z | |
| dc.date.available | 2022-11-02T17:01:48Z | |
| dc.date.created | 2015-11-19T18:57:33Z | |
| dc.date.issued | 2012 | |
| dc.identifier | http://hdl.handle.net/20.500.12104/70931 | |
| dc.identifier | 10.1109/ICEEE.2012.6421191 | |
| dc.identifier | http://www.scopus.com/inward/record.url?eid=2-s2.0-84874440761&partnerID=40&md5=cd1be90f6c6b879b54bac05ed08e5214 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/5024470 | |
| dc.description.abstract | The present paper describes a methodology to estimate the attitude and the position of a bio-inspired robot as well the position of a target. The robot is equipped with a decoupled eye yielding an angular measurement relative to a target and it does not use an IMU. An Extended Kalman Filter is designed to estimate robot and target states. Simulation results show that the estimator is able to converge to the actual states, and reject some perturbations. It is important to highlight that the method assumes that the initial position of the target is unknown. As a consequence no initial guess for the target position is needed. © 2012 IEEE. | |
| dc.relation | CCE 2012 - 2012 9th International Conference on Electrical Engineering, Computing Science and Automatic Control | |
| dc.relation | Scopus | |
| dc.title | State estimation for a bio-inspired hovering robot equipped with an angular sensor | |
| dc.type | Conference Paper | |
