Abstract
For a humanoid robot to safely walk in unknown environments, various sensors are used to identify the surface condition and recognize any obstacles. The humanoid robot is not fixed on the surface and the base/orientation of the kinematics change while it is walking. Therefore, if the foot contact changes from the estimated due to the unknown surface condition, the kinematics results are not correct. The robot may not be able to perform the motion commands based on the incorrect surface condition. Some robots have built-in range sensors but it’s difficult to accurately model the surface from the sensor readings because the movement of the robot should be considered and the robot localization should have zero error for correct interpretation of the sensor readings. In this paper, three infrared range sensors are used in order to perceive the floor state. Covariance analysis is incorporated to consider the uncertainties. The accelerometer and gyro sensor are also used in order to detect the moment a foot hits the surface. This information provides correction to the motion planner and robot kinematics when the environment is not modeled correctly.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
C. Fu and K. Chen, “Gait synthesis and sensory control of stair climbing for a humanoid robot,” IEEE Trans. on Industrial Electronics, vol. 55, no. 5, pp. 2111–2120l, 2008.
J. Y. Kim, I. W. Park, and J. H. Oh, “Walking control algorithm of biped humanoid robot on uneven and inclined floor,” Journal of Intelligent and Robotic Systems, vol. 48, no. 4, pp. 457–484, 2007.
C.-S. Park, T. Ha, J. Kim, and C.-H. Choi, “Trajectory generation and control for a biped robot walking upstairs,” Int. Journal of Control, Automation and Systems, vol. 8, no. 2, pp. 339–351, 2010.
K. Okada, T. Ogura, A. Haneda, and M. Inaba, “Autonomous 3d walking system for a humanoid robot based on visual step recognition and 3D foot step planner,” Proc. of the IEEE International Conference on Robotics and Automation, pp. 623–628, 2005.
J. Gutmann, M. Fukuchi, and M. Fujita, “3D perception and environment map generation for humanoid robot navigation,” Int. Journal of Robotics Research, vol. 27, no. 10, pp. 1117–1134, 2008.
M. Heracles, B. Bolder, and C. Goerick, “Fast detection of arbitrary planar surfaces from unreliable 3D data,” Proc. of IEEE/RSJ Int. Conference on Intelligent Robots and Systems, pp. 5717–5724, 2009.
S. P. N. Singh and K. J. Waldron, “Attitude estimation for dynamic legged locomotion using range and inertial sensors,” Proc. of the Int. Conference on Robotics and Automation, pp. 1663–1668, 2005.
M. Gienger, K. Loffler, and F. Pfeiffer, “Walking control of a biped robot based on inertial measurement,” Proc. of the Third IARP Int. Workshop on Humanoid and Human Friendly Robotics, pp. 22–29, 2002.
H. Rehbinder and X. Hu, “Drift-free attitude estimation for accelerated rigid bodies,” Proc. of the IEEE International Conference on Robotics and Automation, pp. 4244–4249. 2001.
R. Henrik and H. Xiaoming, “Nonlinear pitch and roll estimation for walking robots,” Proc. of the IEEE Int. Conf. on Robotics and Automation, pp. 2617–2622, 2000.
M. Lee and S. Lee, “Design and analysis of an infrared range sensor system for floor-state estimation,” Journal of Mechanical Science and Technology, vol. 25, no. 4, pp. 1043–1050, 2011.
Author information
Authors and Affiliations
Corresponding author
Additional information
Sooyong Lee received his B.S. and M.S. degrees in Mechanical Engineering from Seoul National University, Seoul, Korea, in 1989 and 1991, respectively, and his Ph.D. degree from MIT, Cambridge, MA, in 1996. He worked as a Senior Research Scientist at KIST and then as an Assistant Professor in the Department of Mechanical Engineering at Texas A&M University. He joined Hongik University, Seoul, Korea in 2003 and is currently a Professor in the Mechanical and System Design Engineering Department. His current research includes mobile robot localization and navigation, and active sensing.
Paul Y. Oh received mechanical engineering degrees from McGill (B.Eng 1989), Seoul National (M.Sc 1992), and Columbia (Ph.D. 1999) universities. Paul Oh is a full professor and ASME Fellow at Drexel University’s Mechanical Engineering Department. From 2008–2010, he served at the National Science Foundation (NSF) as the Program Director managing the robotics research portfolio. He has authored over 90 referred archival papers and edited 2 books in the areas of robotics and unmanned systems. Honors include faculty fellowships at NASA Jet Propulsion Lab (2002), Naval Research Lab (2003 and 2013), the NSF CAREER award (2004), the SAE Ralph Teetor Award for Engineering Education Excellence (2005) and being named a Boeing Welliver Fellow (2006). He is the Director of the Drexel Autonomous Systems Lab and also the Founding Chair of the IEEE Technical Committee on Aerial Robotics and UAVs.
Rights and permissions
About this article
Cite this article
Lee, S., Oh, P.Y. Sensor information analysis for a humanoid robot. Int. J. Control Autom. Syst. 13, 175–181 (2015). https://doi.org/10.1007/s12555-013-0519-5
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12555-013-0519-5