I am an experienced robotics and mechatronics engineer having worked on a wide range of medical and industrial engineering research and development projects. In general, I am interested in and passionate about developing and designing custom and complex automation solutions utilizing cutting edge robotics research. This includes using real-time multi-sensor feedback to create intelligent and adaptive robotic and automated systems. I bring this background and passion in systems, mechatronics and software engineering to all my projects.
CAN bus, UART, I2C, ModbusUDP
Particularly in the last 5-6 years, I have gained substantial experience in industrial robotics software engineering and development for custom and specialized robotics applications. In order to facilitate software development and hardware integration, I have leveraged the popular robotics software framework and ecosystem ROS.
Below are descriptions of my current and past projects, as well as the skills and expertise I developed working on them.
Being a lead developer and therefore heavily involved in this project was and continues to be a very rewarding and interesting experience. I gained a lot of additional experience in robotics software design, and mechanical and electrical design. I also gained new experience in product development and design, and the many intricacies involved in creating a viable and user-friendly product while at the same time keeping manufacturing and cost constraints in mind.
This project also gave me the opportunity to directly apply my expertise in robotics software design and development gained during work on previous projects, which helped accelerate the development of the system.
When I first joined the ADaMS lab at the University of Alberta, I began to explore how to execute 3D printing trajectories on industrial manipulators using ROS. With my prior experience with ROS-Industrial-based robot drivers, the kinematics framework MoveIt! and hardware integration via ROS, I was confident that it was possible to develop a software for execution of 3D printing trajectories using software frameworks I was already familiar with from past projects. This initial idea developed into a functional and hardware-agnostic AM software stack for the execution of planar and multi-axis AM trajectories with successful builds of demo components.
The stack has so far been successfully used on different Motoman robot models (MA2010 and SIA5) and a custom, in-house built CNC-based (GRBL) 3-axis cartesian gantry system (see above videos). Initial hardware simulation tests (ABB's RobotStudio) have shown that it is possible to execute the same trajectories on ABB robots, with no modification to the stack. Only a hardware-specific driver is needed. One of the most attractive features of the stack is the hardware-agnostic and modular design that enables the quick integration of different deposition and robotic systems and extension with algorithms for the real-time monitoring and control of the deposition process. A special thank you goes to the students who helped with integration and development of software drivers for some systems. For robotics-centred data structure definitions and trajectory visualization, the stack uses a modified version of the ROS Additive Manufacturing stack.
This project was interesting to work on because it gave me the opportunity to work with and gain detailed experience with the powerful offline robot programming software RoboDK. Especially getting to know the API and post processor implementation gave me valuable insight.
[1] | T. Lehmann, D. Rose, E. Ranjbar, M. Ghasri-Khouzani, M. Tavakoli, H. Henein, T. Wolfe, A. J. Qureshi, Large-scale metal additive manufacturing: a holistic review of the state of the art and challenges, International Materials Reviews, 2021. (Taylor & Francis Online) |
[2] | T. Lehmann, A. Jain, Y. Jain, H. Stainer, T. Wolfe, H. Henein, A. J. Qureshi, Concurrent geometry- and material-based process identification and optimization for robotic CMT-based wire arc additive manufacturing, Materials & Design, vol. 194, p. 108841, Sep. 2020. (Sciencedirect) |
[3] | T. Lehmann, R. Sloboda, N. Usmani, and M. Tavakoli, Model-based Needle Steering in Soft Tissue via Lateral Needle Actuation, IEEE Robotics and Automation Letters, vol. 3, no. 4, pp. 3930-3936, Oct. 2018. Also, selected for presentation at the IEEE/RSJ International Conference on Intelligent Robots and Systems, Madrid, Spain, 2018. (Postprint) (IEEEXplore) |
[4] | T. Lehmann, R. Sloboda, N. Usmani, and M. Tavakoli, Human-machine collaboration modalities for semi-automated needle insertion into soft tissue, IEEE Robotics and Automation Letters, vol. 3, no. 1, pp. 477-483, 2018. (Postprint) (IEEEXplore) |
[5] | T. Lehmann, C. Rossa, N. Usmani, R. Sloboda, and M. Tavakoli, Intraoperative Tissue Young’s Modulus Identification During Needle Insertion Using a Laterally Actuated Needle, IEEE Transactions on Instrumentation and Measurement, vol. 67, no. 2, pp. 371-381, 2018. (Postprint) (IEEEXplore) |
[6] | T. Lehmann, C. Rossa, N. Usmani, R. Sloboda, and M. Tavakoli, Deflection modeling for a needle actuated by lateral force and axial rotation during insertion in soft phantom tissue, Mechatronics, vol. 48, pp. 42-53, 2017. (Postprint) (ScienceDirect) |
[7] | T. Lehmann, C. Rossa, N. Usmani, R. Sloboda and M. Tavakoli, A real-time estimator for needle deflection during insertion into soft tissue based on adaptive modeling of needle-tissue interactions, IEEE/ASME Transactions on Mechatronics, vol. 21, issue 6, pp. 2601-2612, 2016. (Postprint) (IEEEXplore) |
[8] | C. Rossa, T. Lehmann, R. Sloboda, N. Usmani and M. Tavakoli, A data-driven soft sensor for needle deflection in heterogeneous tissue using just-in-time modelling, Medical & Biological Engineering & Computing, pp. 1-14, 2016. (Postprint) (SpringerLink) (SharedIt) |
[9] | J. Kretschmer, B. Laufer, T. Lehmann, P. Stehle, D. Redmond, and K. Möller, Ein softwarebasierter Patientensimulator zur Evaluierung medizinischer Entscheidungssysteme (A software-based patient simulator to evaluate medical decision support systems), at -- Automatisierungstechnik, vol. 64, issue 11, pp. 878-893, 2016. (DeGruyter) |
[10] | P. Stehle, T. Lehmann, D. Redmond, K. Möller, and J. Kretschmer, A java based simulator with user interface to simulate ventilated patients, Current Directions in Biomedical Engineering, vol. 1, no. 1, pp. 423-427, 2015. (DeGruyter) |
[11] | T. Lehmann, M. Tavakoli, N. Usmani and R. Sloboda, Force-Sensor-Based Estimation of Needle Tip Deflection in Brachytherapy, Journal of Sensors, vol. 2013, 2013. (Postprint) (Hindawi) |
[12] | T. Lehmann, C. Rossa, N. Usmani, R. Sloboda and M. Tavakoli, Needle path control during insertion in soft tissue using a force-sensor-based deflection estimator, Proceedings of the 2016 IEEE International Conference on Advanced Intelligent Mechatronics, Banff, Canada, July 12-15, 2016, pp. 1174--1179. (Postprint) (IEEEXplore) |
[13] | J. Kretschmer, T. Lehmann, D. Redmond, P. Stehle and K. Möller, A Modular Patient Simulator for Evaluation of Decision Support Algorithms in Mechanically Ventilated Patients, XIV Mediterranean Conference on Medical and Biological Engineering and Computing 2016 (MEDICON 2016), 2016. (SpringerLink) |
[14] | T. Lehmann, C. Rossa, N. Usmani, R. Sloboda and M. Tavakoli, A virtual sensor for needle deflection estimation during soft-tissue needle insertion, Proceedings of the 2015 IEEE International Conference on Robotics and Automation, Seattle, USA, 2015, pp. 1217-1222. (Postprint) (IEEEXplore) |
[15] | T. Nguyen, T. Lehmann, J. Kretschmer and K. Möller, Bringing model based ventilation therapy to the bedside, 2013 ICME International Conference on Complex Medical Engineering, Beijing, China, 2013, pp. 666-669. (IEEEXplore) |