Mobile robot localization with gyroscope and constrained Kalman filter

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Abstract

The odometry information used in mobile robot localization can contain a significant number of errors when robot experiences slippage. To offset the presence of these errors, the use of a low-cost gyroscope in conjunction with Kalman filtering methods has been considered by many researchers. However, results from conventional Kalman filtering methods that use a gyroscope with odometry can unfeasible because the parameters are estimated regardless of the physical constraints of the robot. In this paper, a novel constrained Kalman filtering method is proposed that estimates the parameters under the physical constraints using a general constrained optimization technique. The state observability is improved by additional state variables and the accuracy is also improved through the use of a nonapproximated Kalman filter design. Experimental results show that the proposed method effectively offsets the localization error while yielding feasible parameter estimation.

Recommended by Editor Jae-Bok Song.
Hyun Myung received his Ph.D. degree in Electrical Engineering from KAIST (Korea Advanced Institute of Science and Technology), Daejeon, South Korea in 1998. He is currently an assistant professor in Dept. of Civil and Environmental Engineering, and also an adjunct professor of Robotics Program and KIUSS (KAIST Institute for Urban Space and Systems) at KAIST. He was a principal researcher in SAIT (Samsung Advanced Institute of Technology, Samsung Electronics Co., Ltd.), Yongin, Republic of Korea (2003.7–2008.2). He was a director in Emersys Corp. (2002.3–2003.6) and a senior researcher in ETRI (Electronics and Telecommunications Research Institute) (1998.9–2002.2), South Korea. His research interests are in the areas of mobile robot navigation, SLAM (Simultaneous Localization And Mapping), evolutionary computation, numerical and combinatorial optimization, and intelligent control based on soft computing techniques.
Hyoung-Ki Lee received his Ph.D. degree in Robotics from KAIST(Korea Advanced Institute of Science and Technology), Daejeon, South Korea in 1998. In 1999, he worked as a Postdoctoral Fellow in Mechanical Engineering Lab., AIST, in Japan. In 2000, he joined Samsung Advanced Institute of Technology and is developing vacuum cleaning robot with localization function as a part of home service robot project. His research interests include SLAM (Simultaneous Localization And Mapping) for home robots fusing different kinds of sensors (inertial sensors, cameras, range finders, etc.) and developing new low-cost sensor modules such as MEMS gyro sensor module and structured light range finder.
Kiwan Choi received his M.S. degree in Mechanical Design and Production Engineering from Seoul National University, South Korea in 1999. He is currently a senior researcher in the Robot Navigation Group, Samsung Advanced Institute of Technology, Samsung Electronics Co., Ltd. His current research interests include SLAM (Simultaneous Localization And Mapping), inertial navigation systems, and mobile robotics.
Seok Won Bang received his B.S. degree in Electrical Engineering from Seoul National University in 1988. He received his M.S and Ph.D. degrees in Electrical Engineering in KAIST(Korea Advanced Institute of Science and Technology) in 1991 and 1996. He worked for Samsung Motors in 1995∼1998 and worked for Samsung Advanced Institute of Technology in 1999–2007. He is with Robotics Institute in Carnegie Mellon University. His research interests include mobile robot navigation, environment perception, and consumer robotics.