Marcel Tresanchez

Measuring Gait Using a Ground Laser Range Sensor

This paper describes a measurement system designed to register the displacement of the legs using a two-dimensional laser range sensor with a scanning plane parallel to the ground and extract gait parameters. In the proposed methodology, the position of the legs is estimated by fitting two circles with the laser points that define their contour and the gait parameters are extracted applying a step-line model to the estimated displacement of the legs to reduce uncertainty in the determination of the stand and swing phase of the gait. Results obtained in a range up to 8 m shows that the systematic error in the location of one static leg is lower than 10 mm with and standard deviation lower than 8 mm; this deviation increases to 11 mm in the case of a moving leg. The proposed measurement system has been applied to estimate the gait parameters of six volunteers in a preliminary walking experiment.

Real-Time Tree-Foliage Surface Estimation Using a Ground Laser Scanner

The optimization of most pesticide and fertilizer applications is based on overall grove conditions. In this paper, we propose a measurement system to estimate the foliage surface of a tree crop. The system is based on a ground laser scanner that estimates the volume of the trees and then extrapolates their leaf area using simple and fast algorithms to allow true real-time operation. Tests with pear trees demonstrated that the relation between the volume and the foliage can be interpreted as linear with a coefficient of correlation (R) of 0.81, and the foliage surface can be estimated from this volume with an average error less than 6%.

Definition of Linear Color Models in the RGB Vector Color Space to Detect Red Peaches in Orchard Images Taken under Natural Illumination

This work proposes the detection of red peaches in orchard images based on the definition of different linear color models in the RGB vector color space. The classification and segmentation of the pixels of the image is then performed by comparing the color distance from each pixel to the different previously defined linear color models. The methodology proposed has been tested with images obtained in a real orchard under natural light. The peach variety in the orchard was the paraguayo (Prunus persica var. platycarpa) peach with red skin. The segmentation results showed that the area of the red peaches in the images was detected with an average error of 11.6%; 19.7% in the case of bright illumination; 8.2% in the case of low illumination; 8.6% for occlusion up to 33%; 12.2% in the case of occlusion between 34 and 66%; and 23% for occlusion above 66%. Finally, a methodology was proposed to estimate the diameter of the fruits based on an ellipsoidal fitting. A first diameter was obtained by using all the contour pixels and a second diameter was obtained by rejecting some pixels of the contour. This approach enables a rough estimate of the fruit occlusion percentage range by comparing the two diameter estimates.

A Proposal for Automatic Fruit Harvesting by Combining a Low Cost Stereovision Camera and a Robotic Arm

This paper proposes the development of an automatic fruit harvesting system by combining a low cost stereovision camera and a robotic arm placed in the gripper tool. The stereovision camera is used to estimate the size, distance and position of the fruits whereas the robotic arm is used to mechanically pickup the fruits. The low cost stereovision system has been tested in laboratory conditions with a reference small object, an apple and a pear at 10 different intermediate distances from the camera. The average distance error was from 4% to 5%, and the average diameter error was up to 30% in the case of a small object and in a range from 2% to 6% in the case of a pear and an apple. The stereovision system has been attached to the gripper tool in order to obtain relative distance, orientation and size of the fruit. The harvesting stage requires the initial fruit location, the computation of the inverse kinematics of the robotic arm in order to place the gripper tool in front of the fruit, and a final pickup approach by iteratively adjusting the vertical and horizontal position of the gripper tool in a closed visual loop. The complete system has been tested in controlled laboratory conditions with uniform illumination applied to the fruits. As a future work, this system will be tested and improved in conventional outdoor farming conditions.

Vineyard Yield Estimation Based on the Analysis of High Resolution Images Obtained with Artificial Illumination at Night

This paper presents a method for vineyard yield estimation based on the analysis of high-resolution images obtained with artificial illumination at night. First, this paper assesses different pixel-based segmentation methods in order to detect reddish grapes: threshold based, Mahalanobis distance, Bayesian classifier, linear color model segmentation and histogram segmentation, in order to obtain the best estimation of the area of the clusters of grapes in this illumination conditions. The color spaces tested were the original RGB and the Hue-Saturation-Value (HSV). The best segmentation method in the case of a non-occluded reddish table-grape variety was the threshold segmentation applied to the H layer, with an estimation error in the area of 13.55%, improved up to 10.01% by morphological filtering. Secondly, after segmentation, two procedures for yield estimation based on a previous calibration procedure have been proposed: (1) the number of pixels corresponding to a cluster of grapes is computed and converted directly into a yield estimate; and (2) the area of a cluster of grapes is converted into a volume by means of a solid of revolution, and this volume is converted into a yield estimate; the yield errors obtained were 16% and −17%, respectively.

Using the Optical Mouse Sensor as a Two-Euro Counterfeit Coin Detector

In this paper, the sensor of an optical mouse is presented as a counterfeit coin detector applied to the two-Euro case. The detection process is based on the short distance image acquisition capabilities of the optical mouse sensor where partial images of the coin under analysis are compared with some partial reference coin images for matching. Results show that, using only the vision sense, the counterfeit acceptance and rejection rates are very similar to those of a trained user and better than those of an untrained user.

Bioinspired electronic white cane implementation based on a LIDAR, a tri-axial accelerometer and a tactile belt

This work proposes the creation of a bioinspired electronic white cane for blind people using the whiskers principle for short-range navigation and exploration. Whiskers are coarse hairs of an animals face that tells the animal that it has touched something using the nerves of the skin. In this work the raw data acquired from a low-size terrestrial LIDAR and a tri-axial accelerometer is converted into tactile information using several electromagnetic devices configured as a tactile belt. The LIDAR and the accelerometer are attached to the user’s forearm and connected with a wire to the control unit placed on the belt. Early validation experiments carried out in the laboratory are promising in terms of usability and description of the environment.

Two-Dimensional Radial Laser Scanning for Circular Marker Detection and External Mobile Robot Tracking

This paper presents the use of an external fixed two-dimensional laser scanner to detect cylindrical targets attached to moving devices, such as a mobile robot. This proposal is based on the detection of circular markers in the raw data provided by the laser scanner by applying an algorithm for outlier avoidance and a least-squares circular fitting. Some experiments have been developed to empirically validate the proposal with different cylindrical targets in order to estimate the location and tracking errors achieved, which are generally less than 20 mm in the area covered by the laser sensor. As a result of the validation experiments, several error maps have been obtained in order to give an estimate of the uncertainty of any location computed. This proposal has been validated with a medium-sized mobile robot with an attached cylindrical target (diameter 200 mm). The trajectory of the mobile robot was estimated with an average location error of less than 15 mm, and the real location error in each individual circular fitting was similar to the error estimated with the obtained error maps. The radial area covered in this validation experiment was up to 10 m, a value that depends on the radius of the cylindrical target and the radial density of the distance range points provided by the laser scanner but this area can be increased by combining the information of additional external laser scanners.

Assistant Personal Robot (APR): Conception and Application of a Tele-Operated Assisted Living Robot.

This paper presents the technical description, mechanical design, electronic components, software implementation and possible applications of a tele-operated mobile robot designed as an assisted living tool. This robotic concept has been named Assistant Personal Robot (or APR for short) and has been designed as a remotely telecontrolled robotic platform built to provide social and assistive services to elderly people and those with impaired mobility. The APR features a fast high-mobility motion system adapted for tele-operation in plain indoor areas, which incorporates a high-priority collision avoidance procedure. This paper presents the mechanical architecture, electrical fundaments and software implementation required in order to develop the main functionalities of an assistive robot. The APR uses a tablet in order to implement the basic peer-to-peer videoconference and tele-operation control combined with a tactile graphic user interface. The paper also presents the development of some applications proposed in the framework of an assisted living robot.

Ambient Intelligence Application Based on Environmental Measurements Performed with an Assistant Mobile Robot

This paper proposes the use of an autonomous assistant mobile robot in order to monitor the environmental conditions of a large indoor area and develop an ambient intelligence application. The mobile robot uses single high performance embedded sensors in order to collect and geo-reference environmental information such as ambient temperature, air velocity and orientation and gas concentration. The data collected with the assistant mobile robot is analyzed in order to detect unusual measurements or discrepancies and develop focused corrective ambient actions. This paper shows an example of the measurements performed in a research facility which have enabled the detection and location of an uncomfortable temperature profile inside an office of the research facility. The ambient intelligent application has been developed by performing some localized ambient measurements that have been analyzed in order to propose some ambient actuations to correct the uncomfortable temperature profile.