State estimation technique for a planetary rover

Given the long traverse times and severe environmental constraints on planet Mars, the only option feasible now is to observe and explore the planet through more sophisticated planetary rovers. To achieve increasingly ambitious mission objectives under such extreme conditions, autonomy for planetary rovers must be continuously enhanced based on the cues and experiences obtained from the current missions. Increased autonomy, obviously, relies on the quality of estimates of rover's state i.e. its position and orientation relative to some starting frame of reference. This thesis encompasses the analyses of different approaches used in planetary rover states estimation. Based on the observations obtained a state estimation approach using Extended Kalman filter based fusion of distance from odometry and attitude from an inertial measurement unit (IMU) has been proposed. To simulate a Sun-sensor-based approach for absolute corrections, a magnetic compass was used to give absolute heading updates. The technique was implemented on MotherBot, a skid steered rover. It showed an error range within 3% of the distance travelled as compared to about 8% error obtained from direct fusion