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A dynamic model for GPS based attitude determination and testing using a serial robotic manipulator

View Article: PubMed Central - PubMed

ABSTRACT

A computational algorithm is developed for estimating accurately the attitude of a robotic arm which moves along a predetermined path. This algorithm requires preliminary input data obtained in the static mode to yield phase observables for the precise, 3-axis attitude determination of a swinging manipulator in the dynamic mode. Measurements are recorded simultaneously by three GPS L1 receivers and then processed in several steps to accomplish this task. First, artkconv batch executable converts GPS receiver readings into RINEX format to generate GPS observables and ephemeris for multiple satellites. Then baseline vectors determination is carried out by baseline constrained Least-Squares Ambiguity Decorrelation (LAMBDA) method that uses double difference carrier phase estimates as input to calculate integer solution for each baseline. Finally, attitude determination is made by employing alternatively Least-squares attitude determination (LSAD) in the static mode and extended Kalman filter in the dynamic mode. The algorithm presented in this paper is applied to recorded data on Mitsubishi RV-M1 robotic arm in order to produce attitude estimates. These results are confirmed by another set of Euler angles independently evaluated from robotic arm postures obtained along the predefined trajectory.

No MeSH data available.


Simulation of the robotic arm movement along roll angle.
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f0015: Simulation of the robotic arm movement along roll angle.

Mentions: At the first stage of the experiments, GPS data were gathered in static mode for two hours for preliminary determination of the baseline lengths between antennas with millimeter-level precision. At the second stage, the manipulator’s end effector altered its attitude at a predefined and constant rotation rate and moved along certain trajectories. The rotations along yaw, roll, and pitch angles in the manipulator’s reference frame were modeled beforehand on Movemaster EX Simulator as shown in Fig. 2, Fig. 3, Fig. 4. Just before starting of these three dynamic tests, corresponding experiments in static modes were carried out to provide the initial attitude angles which were used in the verification analysis afterward.


A dynamic model for GPS based attitude determination and testing using a serial robotic manipulator
Simulation of the robotic arm movement along roll angle.
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5384300&req=5

f0015: Simulation of the robotic arm movement along roll angle.
Mentions: At the first stage of the experiments, GPS data were gathered in static mode for two hours for preliminary determination of the baseline lengths between antennas with millimeter-level precision. At the second stage, the manipulator’s end effector altered its attitude at a predefined and constant rotation rate and moved along certain trajectories. The rotations along yaw, roll, and pitch angles in the manipulator’s reference frame were modeled beforehand on Movemaster EX Simulator as shown in Fig. 2, Fig. 3, Fig. 4. Just before starting of these three dynamic tests, corresponding experiments in static modes were carried out to provide the initial attitude angles which were used in the verification analysis afterward.

View Article: PubMed Central - PubMed

ABSTRACT

A computational algorithm is developed for estimating accurately the attitude of a robotic arm which moves along a predetermined path. This algorithm requires preliminary input data obtained in the static mode to yield phase observables for the precise, 3-axis attitude determination of a swinging manipulator in the dynamic mode. Measurements are recorded simultaneously by three GPS L1 receivers and then processed in several steps to accomplish this task. First, artkconv batch executable converts GPS receiver readings into RINEX format to generate GPS observables and ephemeris for multiple satellites. Then baseline vectors determination is carried out by baseline constrained Least-Squares Ambiguity Decorrelation (LAMBDA) method that uses double difference carrier phase estimates as input to calculate integer solution for each baseline. Finally, attitude determination is made by employing alternatively Least-squares attitude determination (LSAD) in the static mode and extended Kalman filter in the dynamic mode. The algorithm presented in this paper is applied to recorded data on Mitsubishi RV-M1 robotic arm in order to produce attitude estimates. These results are confirmed by another set of Euler angles independently evaluated from robotic arm postures obtained along the predefined trajectory.

No MeSH data available.