HaptiCharger: Robotic Charging of Electric Vehicles Based on Human Haptic Patterns

The growing demand for electric vehicles requires the development of automated car charging methods. At the moment, the process of charging an electric car is completely manual, and that requires physical effort to accomplish the task, which is not suitable for people with disabilities. Typically, the effort in the automation of the charging task research is focused on detecting the position and orientation of the socket, which resulted in a relatively high accuracy, 5 mm, and 10 degrees. However, this accuracy is not enough to complete the charging process. In this work, we focus on designing a novel methodology for robust robotic plug-in and plug-out based on human haptics to overcome the error in the orientation of the socket. Participants were invited to perform the charging task, and their cognitive capabilities were recognized by measuring the applied forces along with the movements of the charger. Eventually, an algorithm was developed based on the human's best strategies to be applied to a robotic arm.Comment: Manuscript accepted to IEEE ROBIO 202

TeslaCharge: Smart Robotic Charger Driven by Impedance Control and Human Haptic Patterns

The growing demand for electric vehicles requires the development of automated car charging methods. At the moment, the process of charging an electric car is completely manual, and that requires physical effort to accomplish the task, which is not suitable for people with disabilities. Typically, the effort in the research is focused on detecting the position and orientation of the socket, which resulted in a relatively high accuracy, $\pm 5 \: mm$ and $\pm 10^o$. However, this accuracy is not enough to complete the charging process. In this work, we focus on designing a novel methodology for robust robotic plug-in and plug-out based on human haptics, to overcome the error in the position and orientation of the socket. Participants were invited to perform the charging task, and their cognitive capabilities were recognized by measuring the applied forces along with the movement of the charger. Three controllers were designed based on impedance control to mimic the human patterns of charging an electric car. The recorded data from humans were used to calibrate the parameters of the impedance controllers: inertia $M_d$, damping $D_d$, and stiffness $K_d$. A robotic validation was performed, where the designed controllers were applied to the robot UR10. Using the proposed controllers and the human kinesthetic data, it was possible to successfully automate the operation of charging an electric car.Comment: Accepted to the 21st IEEE International Conference on Advanced Robotics (ICAR 2023). IEEE copyrigh

Smart Technologies for Precision Assembly

This open access book constitutes the refereed post-conference proceedings of the 9th IFIP WG 5.5 International Precision Assembly Seminar, IPAS 2020, held virtually in December 2020. The 16 revised full papers and 10 revised short papers presented together with 1 keynote paper were carefully reviewed and selected from numerous submissions. The papers address topics such as assembly design and planning; assembly operations; assembly cells and systems; human centred assembly; and assistance methods in assembly

Diseño de grip adaptable a un cobot y a un humano haciendo uso de un destornillador

En la actualidad existen herramientas que se adaptan a los robots colaborativos mediante grippers, pero aún no se ha encontrado evidencia alguna de un diseño de grip que se ajuste tanto al robot colaborativo como a la ergonomía de la mano haciendo uso de un destornillador, adicionalmente el robot colaborativo UR3 de la Pontificia Universidad Javeriana no cumple las funciones colaborativas con un humano respecto a la tarea de atornillar o desatornillar. Para darle solución a este problema se propone un diseño de grip que consta de dos partes, la primera parte está basada en un mango cilíndrico de destornillador con superficie antiderrapante y la segunda parte cuenta con dos ranuras en la cara superior para que el gripper del cobot pueda adaptarse al grip.Currently there are tools that are adapted to collaborative robots through grippers, but there has not been yet any evidence of a grip design that fits both the collaborative robot and the ergonomics of the hand by using a screwdriver, furthermore the collaborative robot UR3 of the Pontificia Universidad Javeriana does not fulfill the collaborative functions with a human regarding the task of screwing or unscrewing. To solve this problem, a grip design consisting of two parts is proposed. The first part is based on a cylindrical screwdriver handle with anti-skid surface and the second part has two grooves on the upper side so that the gripper of the cobot can adapt to the grip.Ingeniero (a) IndustrialPregrad