Ocular Robotics 3D LIDAR Scanning Systems

A description and demonstration of the unique capabilities of the Ocular Robotics 3D LIDAR Scanner range.

RE05 3D LIDAR & REV25 VISION – RGB Point Cloud Demonstration

This video initially shows capture of a panorama using the REV25 camera system. No stitching is used in generating this panorama we simply use the pointing precision of the REV25 to acquire the images and display them directly on the screen. At the same time we use the RE05 to acquire a 3D point cloud of the same area.

Photonics West 2014 Demonstration – Edmund Optics

Ocular Robotics collaborated with Edmund Optics, supplier of key optical elements of our systems, on this demonstration at Photonics West 2014 in February. Ocular Robotics Dr David Wood explains the two parts of the demonstration, firstly where data from our RobotEye VISION REV25 and RobotEye RE05 3D LIDAR systems is fused to produce an RBG point cloud. The second part of the demonstration shows the REV25 vision system rapidly monitoring several different locations with some of them being actively moved on each cycle.

RobotEye RE05 on Italian National Television

Mapping and digitizing archaeological sites is an important task to preserve cultural heritage and to make it accessible to the public. Current systems for digitizing sites typically build upon static 3D laser scanning technology that is brought into archaeological sites by humans. This is acceptable in general, but prevents the digitization of sites that are inaccessible by humans. In the field of robotics, however, there has recently been a tremendous progress in the development of autonomous robots that can access hazardous areas. ROVINA aims at extending this line of research with respect to reliability, accuracy and autonomy to enable the novel application scenario of autonomously mapping of areas of high archaeological value that are hardly accessible.

Ocular Robotics RobotEye LIDAR scan animation

This is a animation of a LIDAR scan using the Ocular Robotics RobotEye RE05 sensor. The scan is of the Great Hall in Sydney, Australia. The data is animated as the sensor does a full field sweep from -35 to +35 degrees elevation. The animation is not displayed in real time. The animation was produced using ParaView. This work was produced as part of the PCL Ocular Robotics code sprint.

RobotEye RE05 Waterfall Scan

Point cloud data is obtained by measuring the waterfall with the RE05 and displayed in PointCloudStudio. The position and direction of the point of view is manipulated with the mouse, looking at the data from various directions. In addition, the point size can be changed so it is easier to see, depending on the viewing position.

RobotEye RE05 Harbor Scan

Point cloud data is obtained by measuring the harbor with the RE05 and displayed in PointCloudStudio. Since the ship was moving on the sea during the measurement, the data is slightly skewed. The overall length of the boat can be measured by specifying two points on the point cloud. The angle between the rope can be measured by specifying three points. By specifying three points on the ground, the height of the truck can be measured.

RobotEye RE05 Rice Field Scan

Point cloud data is obtained by measuring the countryside with the RE05 and displayed in PointCloudStudio. As the plant reflects the laser well, the details in the measured rice field are clean and well defined. By cutting out a portion of the point cloud and specifying the ground by selecting a reference point on it, the persons height and the depth of the moat can be measured.

RobotEye RE05 Office Scan

Point cloud data is obtained with the RE05 and displayed in PointCloudStudio. A variety of filters are then laid over the point cloud. The first filter normalizes the laser reflection intensity, which corrects the relationship between color and reflection intensity. The second filter averages the variation in distance measurement. The third filter performs a process to remove the noise such as removing outliers. The fourth filter, thins out the point cloud, reducing the data size.

RobotEye RE05 Room Scan

How to remove unnecessary point from the point cloud using PointCloudStudio. Data displayed was obtained by measuring a wide space using the RE05. A cut out in the peripheral of the measurement is due to people walking around, these can be removed by specifying the range in which you want to delete. The unwanted points can be removed easily using this two-stage process.

RobotEye RE05 Room Scan Part 2

In PointCloudStudio, points can be added to the point cloud. Data displayed was obtained by measuring a wide space with the RE05. The blind spots of the instrument will cause a hole in the data but by creating several triangles by specifying a few points, these holes can be covered. In addition, poles can be added by specifying two points. This can be used as a marker in the point cloud.

RobotEye RE05 Warehouse Scan

Point cloud integration in PointCloudStudio. The data seen was measured in a warehouse using an RE05. When measuring the data, three high intensity laser reflectors were arranged, which were measured in the two data sets. The co-ordinates of the three data points are used to align the data sets in the integration. Each of the data sets are then correlated and automatically adjusted to overlap nicely. Finally, the two data sets and now fused together to create a single data set.

RobotEye RE05 City Scan

Point cloud integration in PointCloudStudio. The data shown was measured in the city with the RE05. By specifying a shared point within the two data sets, the co-ordinates of these points are used to integrate the two data sets. By calculating the correlation of the points of each data set, automatic adjustments are made to achieve clean overlaps.

RobotEye RE05 City Scan Part 2

Using PointCloudStudio multiple data sets can be integrated. By changing the location of the RE05, 11 data sets were measured one after the other. The extra points due to the overlap when integrating the data can be filtered and removed.