Simultaneous Parameter Calibration, Localization, and Mapping

The calibration parameters of a mobile robot play a substantial role in navigation tasks. Often these parameters are subject to variations that depend either on changes in the environment or on the load of the robot. In this paper, we propose an approach to simultaneously estimate a map of the environment, the position of the on-board sensors of the robot, and its kinematic parameters. Our method requires no prior knowledge about the environment and relies only on a rough initial guess of the parameters of the platform. The proposed approach estimates the parameters online and it is able to adapt to non-stationary changes of the configuration. We tested our approach in simulated environments and on a wide range of real-world data using different types of robotic platforms. (C) 2012 Taylor & Francis and The Robotics Society of Japa

Extrinisic Calibration of a Camera-Arm System Through Rotation Identification

Determining extrinsic calibration parameters is a necessity in any robotic system composed of actuators and cameras. Once a system is outside the lab environment, parameters must be determined without relying on outside artifacts such as calibration targets. We propose a method that relies on structured motion of an observed arm to recover extrinsic calibration parameters. Our method combines known arm kinematics with observations of conics in the image plane to calculate maximum-likelihood estimates for calibration extrinsics. This method is validated in simulation and tested against a real-world model, yielding results consistent with ruler-based estimates. Our method shows promise for estimating the pose of a camera relative to an articulated arm's end effector without requiring tedious measurements or external artifacts. Index Terms: robotics, hand-eye problem, self-calibration, structure from motio

Eye Tracker Accuracy: Quantitative Evaluation of the Invisible Eye Center Location

Purpose. We present a new method to evaluate the accuracy of an eye tracker based eye localization system. Measuring the accuracy of an eye tracker's primary intention, the estimated point of gaze, is usually done with volunteers and a set of fixation points used as ground truth. However, verifying the accuracy of the location estimate of a volunteer's eye center in 3D space is not easily possible. This is because the eye center is an intangible point hidden by the iris. Methods. We evaluate the eye location accuracy by using an eye phantom instead of eyes of volunteers. For this, we developed a testing stage with a realistic artificial eye and a corresponding kinematic model, which we trained with {\mu}CT data. This enables us to precisely evaluate the eye location estimate of an eye tracker. Results. We show that the proposed testing stage with the corresponding kinematic model is suitable for such a validation. Further, we evaluate a particular eye tracker based navigation system and show that this system is able to successfully determine the eye center with sub-millimeter accuracy. Conclusions. We show the suitability of the evaluated eye tracker for eye interventions, using the proposed testing stage and the corresponding kinematic model. The results further enable specific enhancement of the navigation system to potentially get even better results

Measurement of a Metallicity Gradient in a z=2 Galaxy: Implications for Inside-Out Assembly Histories

We present near-infrared imaging spectroscopy of the strongly-lensed z=2.00 galaxy SDSS J120601.69+514227.8 (`the Clone arc'). Using OSIRIS on the Keck 2 telescope with laser guide star adaptive optics, we achieve resolved spectroscopy with 0.20 arcsecond FWHM resolution in the diagnostic emission lines [O III], Halpha, and [N II]. The lensing magnification allows us to map the velocity and star formation from Halpha emission at a physical resolution of ~300 pc in the galaxy source plane. With an integrated star formation rate of ~50 Msun/yr, the galaxy is typical of sources similarly studied at this epoch. It is dispersion-dominated with a velocity gradient of +/- 80 km/s and average dispersion sigma = 85 km/s; the dynamical mass is 2.4 \times 10^{10} Msun within a half-light radius of 2.9 kpc. Robust detection of [N II] emission across the entire OSIRIS field of view enables us to trace the gas-phase metallicity distribution with 500 pc resolution. We find a strong radial gradient in both the [N II]/Halpha and [O III]/Halpha ratios indicating a metallicity gradient of -0.27 +/- 0.05 dex/kpc with central metallicity close to solar. We demonstrate that the gradient is seen independently in two multiple images. While the physical gradient is considerably steeper than that observed in local galaxies, in terms of the effective radius at that epoch, the gradient is similar. This suggests that subsequent growth occurs in an inside-out manner with the inner metallicity gradient diminished over time due to radial mixing and enrichment from star formation.Comment: 6 pages, 4 figures, accepted by ApJ Letter

A framework for flexible integration in robotics and its applications for calibration and error compensation

Robotics has been considered as a viable automation solution for the aerospace industry to address manufacturing cost. Many of the existing robot systems augmented with guidance from a large volume metrology system have proved to meet the high dimensional accuracy requirements in aero-structure assembly. However, they have been mainly deployed as costly and dedicated systems, which might not be ideal for aerospace manufacturing having low production rate and long cycle time. The work described in this thesis is to provide technical solutions to improve the flexibility and cost-efficiency of such metrology-integrated robot systems. To address the flexibility, a software framework that supports reconfigurable system integration is developed. The framework provides a design methodology to compose distributed software components which can be integrated dynamically at runtime. This provides the potential for the automation devices (robots, metrology, actuators etc.) controlled by these software components to be assembled on demand for various assembly applications. To reduce the cost of deployment, this thesis proposes a two-stage error compensation scheme for industrial robots that requires only intermittent metrology input, thus allowing for one expensive metrology system to be used by a number of robots. Robot calibration is employed in the first stage to reduce the majority of robot inaccuracy then the metrology will correct the residual errors. In this work, a new calibration model for serial robots having a parallelogram linkage is developed that takes into account both geometric errors and joint deflections induced by link masses and weight of the end-effectors. Experiments are conducted to evaluate the two pieces of work presented above. The proposed framework is adopted to create a distributed control system that implements calibration and error compensation for a large industrial robot having a parallelogram linkage. The control system is formed by hot-plugging the control applications of the robot and metrology used together. Experimental results show that the developed error model was able to improve the 3 positional accuracy of the loaded robot from several millimetres to less than one millimetre and reduce half of the time previously required to correct the errors by using only the metrology. The experiments also demonstrate the capability of sharing one metrology system to more than one robot