One of the most challenging problems in robot-assisted surgical systems is to provide surgical realism at interactive simulation rates. The proposed visual tracking system can track and register object deformations in real time using a physically based formulation, despite the occlusions produced by the robotic system itself. The results obtained provide an accurate visual representation of the deformed solid and will thus enable new assistance approaches to help surgeons during surgical procedures.

Photogrammetry methods are being used more and more as a 3D technique for large scale metrology applications in industry. Optical targets are placed on an object and images are taken around it, where measuring traceability is provided by precise off-process pre-calibrated digital cameras and scale bars. According to the 2D target image coordinates, target 3D coordinates and camera views are jointly computed. One of the applications of photogrammetry is the measurement of raw part surfaces prior to its machining. For this application, post-process bundle adjustment has usually been adopted for computing the 3D scene. With that approach, a high computation time is observed, leading in practice to time consuming and user dependent iterative review and re-processing procedures until an adequate set of images is taken, limiting its potential for fast, easy-to-use, and precise measurements. In this paper, a new efficient procedure is presented for solving the bundle adjustment problem in portable photogrammetry. In-process bundle computing capability is demonstrated on a consumer grade desktop PC, enabling quasi real time 2D image and 3D scene computing. Additionally, a method for the self-calibration of camera and lens distortion has been integrated into the in-process approach due to its potential for highest precision when using low cost non-specialized digital cameras. Measurement traceability is set only by scale bars available in the measuring scene, avoiding the uncertainty contribution of off-process camera calibration procedures or the use of special purpose calibration artifacts. The developed self-calibrated in-process photogrammetry has been evaluated both in a pilot case scenario and in industrial scenarios for raw part measurement, showing a total in-process computing time typically below 1 s per image up to a maximum of 2 s during the last stages of the computed industrial scenes, along with a relative precision of 1/10,000 (e.g. 0.1 mm error in 1 m) with an error RMS below 0.2 pixels at image plane, ranging at the same performance reported for portable photogrammetry with precise off-process pre-calibrated cameras.

The Automated six Degrees of Freedom (DoF) definition of industrial components has become an added value in production processes as long as the required accuracy is guaranteed. This is where multi-camera systems are finding their niche in the market. These systems provide, among other things, the ease of automating tracking processes without human intervention and knowledge about vision and/or metrology. In addition, the cost of integrating a new sensor into the complete system is negligible compared to other multi-tracker systems. The increase in information from different points of view in multi-camera systems raises the accuracy, based on the premise that the more points of view, the lower the level of uncertainty. This work is devoted to the calibration procedures of multi-camera systems, which is decisive to achieve high performance, with a particular focus on the uncertainty budget. Moreover, an evaluation methodology has been carried out, which is key to determining the level of accuracy of the measurement system.

Robotic arms are widely used in sectors such as automotive or assembly logistics due to their flexibility and cost. Other manufacturing sectors would like to take advantage of this technology, however, higher accuracy is required for their purposes. This paper integrated a multi-camera system to achieve the requirements for milling and drilling tasks in aeronautic parts. A closed-loop framework allows the position of the robot’s end-effector to be corrected with respect to a static reference. This is due to the multi-camera system tracking the position of both elements due to the passive targets on their surface. The challenge is to find an auxiliary system to measure these targets with an uncertainty that allows the desired accuracy to be achieved in high volumes (>3 m³). Firstly, in a reduced scenario, a coordinate measuring machine (CMM), a laser tracker (LT), and portable photogrammetry (PP) have been compared following the guidelines from VDI/VDE 2634-part 1. The conclusions allowed us to jump into an industrial scenario and run a similar test with a higher payload than in the laboratory. The article ends with an application example demonstrating the suitability of the solution.

A photogrammetry-based error compensation solution, comprising calibration, positioning compensation and accuracy validation methodologies, is presented to the aerospace sector, able to assist industrial robots in manufacturing new composite materials, offering versatility and reconfigurability at a lower cost than that resulting from the currently used milling machines. Against a ground truth measured by a laser tracker, it has boosted, in real time, the accuracy level from ±0.685 to ±0.203 mm, on average, and from ±1.621 to ±0.498 mm at peak, following the ISO 9283 standard, and from ±0.534 to ±0.080 mm, on average, and from ±1.804 to ±0.456 mm at peak, with a real part in a large volume under industrial operating conditions, taking into account occlusions and showing robustness against the impact of the payload, the waviness, and the backlash.