Research Article
Year 2018,
Issue: 4, 50 - 55, 04.12.2018
Abstract
The
paper considers walking in-pipe robots, which represent a novel class of in-pipe
robots, with better agility but also a more complicated control compared with
other, more prevalent in-pipe robot types. The focus of the paper is on the
inverse kinematics (IK) of these robots. IK for walking in-pipe robots is a
difficult problem due to a combination of factors, such as joint limits,
multiple possible kinematic singularities, as well as a significant number of
joints that these robots have. All this requires the use of an algorithm that
could take into account multiple objectives and constraints when solving the
problem, and provide a solution in real time using on-board computers. Existing
approaches can achieve this with local linearization of both the objective
function and the constraints; alternatively they do it by taking the constraints
into account. In this work, the IK is transformed into a quadratic program.
Instead of linearizing the objective function, here the orientations of the
robot’s links are approximated by convex combinations of rotation matrices.
This allows relaxing the constraints associated with the special orthogonal
group, placed on the matrices describing the links’ orientation. The paper
shows the form of the resulting quadratic program, discusses the practical
aspects of using this approach and lists its limitations.
References
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Year 2018,
Issue: 4, 50 - 55, 04.12.2018
Abstract
References
- Bloesch, M., Hutter, M., Hoepflinger, M. A., Leutenegger, S., Gehring, C., Remy, C. D., & Siegwart, R. (2013). State estimation for legged robots-consistent fusion of leg kinematics and IMU. Robotics, 17, 17-24. Brown, L., Carrasco, J., Watson, S., & Lennox, B. (2018). Elbow Detection in Pipes for Autonomous Navigation of Inspection Robots. Journal of Intelligent & Robotic Systems, 1-15. Buss, S. R. (2004). Introduction to inverse kinematics with jacobian transpose, pseudoinverse and damped least squares methods. IEEE Journal of Robotics and Automation, 17(1-19), 16. Chang, P. (1987). A closed-form solution for inverse kinematics of robot manipulators with redundancy. IEEE Journal on Robotics and Automation, 3(5), 393-403. Dai, H., Izatt, G., & Tedrake, R. (2017). Global inverse kinematics via mixed-integer convex optimization. In International Symposium on Robotics Research, Puerto Varas, Chile (pp. 1-16). D'Souza, A., Vijayakumar, S., & Schaal, S. (2001). Learning inverse kinematics. In Intelligent Robots and Systems, 2001. Proceedings. 2001 IEEE/RSJ International Conference on(Vol. 1, pp. 298-303). IEEE. Gálvez, J. A., De Santos, P. G., & Pfeiffer, F. (2001). Intrinsic tactile sensing for the optimization of force distribution in a pipe crawling robot. IEEE/ASME Transactions on mechatronics, 6(1), 26-35. Jatsun, S., Savin, S., Lushnikov, B., & Yatsun, A. (2016). Algorithm for motion control of an exoskeleton during verticalization. In ITM Web of Conferences (Vol. 6). EDP Sciences. Jun, C., Deng, Z., & Jiang, S. (2004, August). Study of locomotion control characteristics for six wheels driven in-pipe robot. In Robotics and Biomimetics, 2004. ROBIO 2004. IEEE International Conference on (pp. 119-124). IEEE. Mason, S., Righetti, L., & Schaal, S. (2014, November). Full dynamics LQR control of a humanoid robot: An experimental study on balancing and squatting. In Humanoid Robots (Humanoids), 2014 14th IEEE-RAS International Conference on (pp. 374-379). IEEE. Pfeiffer, F. (2007). The TUM walking machines. Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences, 365(1850), 109-131. Roh, S. G., Lee, J. S., Moon, H., & Choi, H. R. (2009). In-pipe robot based on selective drive mechanism. International Journal of Control, Automation and Systems, 7(1), 105-112. Savin, S. (2017, June). An algorithm for generating convex obstacle-free regions based on stereographic projection. In Control and Communications (SIBCON), 2017 International Siberian Conference on (pp. 1-6). IEEE. Savin, S., Jatsun, S., & Vorochaeva, L. (2017). Trajectory generation for a walking in-pipe robot moving through spatially curved pipes. In MATEC Web of Conferences (Vol. 113, p. 02016). EDP Sciences. Savin, S., Jatsun, S., & Vorochaeva, L. (2017, November). Modification of Constrained LQR for Control of Walking in-pipe Robots. In Dynamics of Systems, Mechanisms and Machines (Dynamics), 2017 (pp. 1-6). IEEE. Savin, S., Jatsun, S., & Vorochaeva, L. (2018). State observer design for a walking in-pipe robot. In MATEC Web of Conferences (Vol. 161, p. 03012). EDP Sciences. Savin, S., & Vorochaeva, L. (2017, June). Footstep planning for a six-legged in-pipe robot moving in spatially curved pipes. In Control and Communications (SIBCON), 2017 International Siberian Conference on (pp. 1-6). IEEE. Savin, S., & Vorochaeva, L. (2017, May). Pace pattern generation for a pipeline robot. In Industrial Engineering, Applications and Manufacturing (ICIEAM), 2017 International Conference on (pp. 1-6). IEEE. Savin, S., & Vorochaeva, L. (2017, May). Nested quadratic programming-based controller for pipeline robots. In Industrial Engineering, Applications and Manufacturing (ICIEAM), 2017 International Conference on (pp. 1-6). IEEE. Sentis, L., & Khatib, O. (2005). Synthesis of whole-body behaviors through hierarchical control of behavioral primitives. International Journal of Humanoid Robotics, 2(04), 505-518. Thielemann, J. T., Breivik, G. M., & Berge, A. (2008, June). Pipeline landmark detection for autonomous robot navigation using time-of-flight imagery. In Computer Vision and Pattern Recognition Workshops, 2008. CVPRW'08. IEEE Computer Society Conference on (pp. 1-7). IEEE. Tsubouchi, T., Takaki, S., Kawaguchi, Y., & Yuta, S. I. (2000). A straight pipe observation from the inside by laser spot array and a TV camera. In Intelligent Robots and Systems, 2000.(IROS 2000). Proceedings. 2000 IEEE/RSJ International Conference on (Vol. 1, pp. 82-87). IEEE. Zagler, A., & Pfeiffer, F. (2003, September). "MORITZ" a pipe crawler for tube junctions. In Robotics and Automation, 2003. Proceedings. ICRA'03. IEEE International Conference on (Vol. 3, pp. 2954-2959). IEEE.
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Details
| Primary Language | English |
|---|---|
| Subjects | Engineering |
| Journal Section | Articles |
| Authors | |
| Publication Date | December 4, 2018 |
| Published in Issue | Year 2018Issue: 4 |
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