Towards cognitive navigation:A biologically inspired calibration mechanism for the head direction cell network

To derive meaningful navigation strategies,animals have to estimate their directional headings in the environment.Accordingly,this function is achieved by the head direction cells that were found in mammalian brains,whose neural activities encode one’s heading direction.It is believed that such head direction information is generated by integrating self-motion cues,which also introduces accumulative errors in the long term.To eliminate such errors,this paper presents an efficient calibration model that mimics the animals’behavior by exploiting visual cues in a biologically plausible way,and then implements it in robotic navigation tasks.The proposed calibration model allows the agent to associate its head direction and the perceived egocentric direction of a visual cue with its position and orientation,and therefore to calibrate the head direction when the same cue is viewed again.We examine the proposed head direction calibration model in extensive simulations and real-world experiments and demonstrate its excellent performance in terms of quick association of information to proximal or distal cues as well as accuracy of calibrating the integration errors of the head direction.Videos can be viewed at https://videoviewsite.wixsite.com/hdc-calibration.

Rotary axis calculation for five-axis FDM printer using a point-fitting optimization method

This paper presents an optimization method to compute the rotary axes of a 5-axis FDM printer whose A-and C-axes have large deviations relative to the x-and z-directions.The optimization model is designed according to the kinematic model in which a point rotates around a spatial line in the machine coordinate system of the printer.The model considers the A-and C-axes as two spatial lines.It is a two-object optimization model including two aspects.One is that the sum of deviations between the measured and computed points should be small;the other is that the deviations should be uniformly distributed for every measured point.A comparison of the new optimization method with conventional error-compensation methods reveals that the former has higher location accuracy.Using the optimized AC axes,5-axis 3D printing paths are planned for some complex workpieces.Data analysis and printing samples show that the optimized AC axes satisfy 5-axes FDM printing requirements for nozzles with a diameter of 1.0 mm.

Error analysis and calibration for underwater sound intensity measuring system

Based on measuring the cross-spectrum density of sound pressure between two hydrophones, the facility for underwater sound intensity measurement is investigated and designed. According to the principle of two-hydrophone method for intensity measurement, the error analysis is carried out. Given the method of sound intensity measurement calibration for this underwater sound intensity measurement facility, the uncertainty of intensity measurement by this facility is evaluated. It is shown that the analysis and evaluation are agreeable to the experimental results.

Calibration of robotic drilling systems with a moving rail

Industrial robots are widely used in aircraft assembly systems such as robotic drilling systems. It is necessary to expand a robot＇s working range with a moving rail. A method for improving the position accuracy of an automated assembly system with an industrial robot mounted on a moving rail is proposed. A multi-station method is used to control the robot in this study. The robot only works at stations which are certain positions defined on the moving rail. The calibration of the robot system is composed by the calibration of the robot and the calibration of the stations.The calibration of the robot is based on error similarity and inverse distance weighted interpolation.The calibration of the stations is based on a magnetic strip and a magnetic sensor. Validation tests were performed in this study, which showed that the accuracy of the robot system gained significant improvement using the proposed method. The absolute position errors were reduced by about 85%to less than 0.3 mm compared with the maximum nearly 2 mm before calibration.

Consistency correction of echo intensity data for multiple radar systems and its application in quantitative estimation of typhoon precipitation

Calibration error is one of the primary sources of bias in echo intensity measurements by ground-based radar systems.Calibration errors cause data discontinuity between adjacent radars and reduce the effectiveness of the radar system.The Global Precipitation Measurement Kuband Precipitation Radar(GPM KuPR)has been shown to provide stable long-term observations.In this study,GPM KuPR observations were converted to S-band approximations,which were then matched spatially and temporally with ground-based radar observations.The measurements of stratiform precipitation below the melting layer collected by the KuPR during Typhoon Ampil were compared with those of multiple radar systems in the Yangtze River Delta to determine the deviations in the echo intensity between the KuPR and the ground-based radar systems.The echo intensity data collected by the ground-based radar systems was corrected using the KuPR observations as reference,and the correction results were verified by comparing them with rain gauge observations.It was found that after the correction,the consistency of the echo intensity measurements of the multiple radar systems improved significantly,and the precipitation estimates based on the revised ground-based radar observations were closer to the rain gauge measurements.