C-Legged Hexapod Robot Design Guidelines Based on Energy Analysis
Source abstract
Abstract
C-legged hexapod robots offer a balanced trade-off between the robust stability of wheeled robots and the increased-motion capabilities of legged robots, and therefore, are currently of great interest. This article investigates the impact of mass, leg radius, and angular velocity on the energy consumption of C-legged hexapod robots, in order to develop a set of design guidelines that maximize the robot’s performance. The kinematic model of a single C-leg system is obtained and used to determine the system’s energy consumption associated with gravitational potential energy (GPE) and kinetic energy (KE) variations. Both the kinematic model and energy model are validated in a custom-made test bench. Our results show that the kinematic model very accurately predicts the trajectory of the system in space, but due to the varying load experienced by the motor, the system lags compared to the model predictions. Furthermore, the energy model has been also validated experimentally and successfully predicts the motor consumption periods. Using the energy model, it has been concluded that the angular velocity of the leg and the leg radius have an exponential relationship with motor peak power demand—directly affecting the motor selection. On the other hand, the mass is inversely proportional to the robot efficiency, and therefore, must be kept as low as possible.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Robotic Locomotion and Control · Prosthetics and Rehabilitation Robotics · Biomimetic flight and propulsion mechanisms
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Centro de Automática y Robótica (UPM-CSIC), Universidad Politécnica de Madrid, 28006 Madrid, Spain
Funding
Ministerio de Ciencia e Innovación · Comunidad de Madrid
References (26)
Show source-provided references
1. Li, Y., Ge, S., Dai, S., Zhao, L., Yan, X., Zheng, Y., and Shi, Y. (2020). Kinematic Modeling of a Combined System of Multiple Mecanum-Wheeled Robots with Velocity Compensation. Sensors, 20.10.3390/s20010075 ↗
2. Jahn, U., Heß, D., Stampa, M., Sutorma, A., Röhrig, C., Schulz, P., and Wolff, C. (2020). A Taxonomy for Mobile Robots: Types, Applications, Capabilities, Implementations, Requirements, and Challenges. Robotics, 9.10.3390/robotics9040109 ↗
3. Review article: Locomotion systems for ground mobile robots in unstructured environments10.5194/ms-3-49-2012 ↗
4. Yang, K., Rong, X., Zhou, L., and Li, Y. (2019). Modeling and Analysis on Energy Consumption of Hydraulic Quadruped Robot for Optimal Trot Motion Control. Appl. Sci., 9.10.3390/app9091771 ↗
5. Bourla, A., Mouchabac, S., El Hage, W., and Ferreri, F. (2018). e-PTSD: An overview on how new technologies can improve prediction and assessment of Posttraumatic Stress Disorder (PTSD). Eur. J. Psychotraumatol., 9.10.1080/20008198.2018.1424448 ↗
6. A Historical Perspective of Legged Robots10.1177/1077546307078276 ↗
7. An Overview of Legged Robots
8. Controlled passive dynamic running experiments with the ARL-monopod II10.1109/TRO.2006.878935 ↗
9. Development of Hexapod Robot with Manoeu-vrable Wheel
10. Moore, E.Z. (2002). Leg Design and Stair Climbing Control for the RHex Robotic Hexapod Leg Design and Stair Climbing Control for the RHex R obotic Hexapod. [Master’s Thesis, McGill University].
11. De León, J., Cebolla, R., and Barrientos, A. (2020). A Sensor Fusion Method for Pose Estimation of C-Legged Robots. Sensors, 20.10.3390/s20236741 ↗
12. RHex: A Simple and Highly Mobile Hexapod Robot10.1177/02783640122067570 ↗
13. Wettergreen, D., and Thorpe, C. (2005, January 2–6). Gait Generation For Legged Robots. Proceedings of the 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, Edmonon, AB, Canada.10.1109/IROS.1992.594568 ↗
14. Minimizing the Energy Consumption for a Hexapod Robot Based on Optimal Force Distribution10.1109/ACCESS.2019.2962527 ↗
15. Bhounsule, P.A., Cortell, J., and Ruina, A. (2012). Design and control of ranger: An energy-efficient, dynamic walking robot. Adaptive Mobile Robotics, Proceedings of the 15th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines (CLAWAR 2012), Baltimore, MD, USA, 23–26 July 2012, World Scientific.10.1142/9789814415958_0057 ↗
16. Design of Leg Wheel Hybrid Hexapod with C-Leg Analysis10.4028/www.scientific.net/AMM.852.832 ↗
17. Improving walking-robot performances by optimizing leg distribution10.1007/s10514-007-9045-8 ↗
18. A literature review on the optimization of legged robots10.1177/1077546311403180 ↗
19. Energy-efficient walking over irregular terrain: A case of hexapod robot10.24425/mms.2019.130562 ↗
20. Dynamic modeling and torque distribution of a climbing hexapod robot10.1007/978-3-319-18126-4_13 ↗
21. Weingarten, J., and Buehler, M. (2003, January 14–19). Gait generation and optimization for legged robots. In Proccedings of the 2003 IEEE International Conference on Robotics and Automation. Taipei, Taiwan. Available online: http://kodlab.seas.upenn.edu/uploads/Kod/Weingarten03.pdf.
22. Luneckas, M., Luneckas, T., Kriaučiūnas, J., Udris, D., Plonis, D., Damaševičius, R., and Maskeliūnas, R. (2021). Hexapod Robot Gait Switching for Energy Consumption and Cost of Transport Management Using Heuristic Algorithms. Appl. Sci., 11.10.3390/app11031339 ↗
23. Carbone, G., and Ceccarelli, M. (2005). Legged Robotic Systems. Cut. Edge Robot.10.5772/4669 ↗
24. Childs, P.R.N. (2019). Worm gears. Mechanical Design Engineering Handbook, Butterworth-Heinemann.10.1016/B978-0-08-102367-9.00011-1 ↗
25. Kapelevich, A.L., and Taye, E. (2010, January 17–19). Self-locking gears: Design and potential applications. Proceedings of the American Gear Manufactures Association Fall Technical Meeting 2010, Milwaukee, WI, USA.
26. (2020). Curve Fitting Toolbox, MathWorks.