Department Publications

This paper introduces techniques for designing and implementing remotely controllable outdoor robots with the ability to localize itself while traversing in hazardous environments. The robot platform designed is a semi-autonomous tiller modified as required by the application. Localization based on wireless sensor network which has been a research interest of is addressed here with the use of Zigbee protocol. A Kalman filter was applied for the initial gathering of training data. For the improvement of the accuracy of position estimation, a fuzzy inference system is introduced. An extended Kalman filter is applied at the end in order to fuse the encoder data with the filtered RSS data. Results prove that a metric accuracy varying from 2m to 10m is achievable depending on the location of the robot with respect to the sensor nodes.

Developing autonomous mobile robots that can coexist with human in populated environments is still considered a big challenge. To address this problem the authors propose a novel scheme to assist mobile robots by providing localization information externally. This scheme combines the autonomous navigation and target tracking research fields to arrive at a structured assistance system for autonomous mobile robots. In the proposed scheme, the environment is sensed using a laser range finder and a camera based sensor unit. Using the Rao-Blackwellized particle filter technique, the robots that need assistance are continuously tracked. In contrast with conventional laser range finder based tracking systems, the placement of the sensor is changed to a level above average human height and the mobile robots are modified by attaching a cylindrical pole. The experiments showed the validity of the proposed …

A novel single-integral representation for the bivariate Rician distribution was presented in a recent letter in this Transactions (ibid., vol. 59, no. 11. pp. 2951-2954, Nov. 2011). The expression given for the bivariate Rician probability density function (PDF) [1, eq. (12a)] contains a typographical error. The correct expression for the bivariate Rician PDF is presented here.

Real Time Location Estimation systems (RTLS) developed for outdoor environments have shown significant errors due to changes in atmospheric conditions, multipath propagation and inherent signal strength variations. In this paper, we present an improved Wi-Fi based RTLS solution for the outdoors that reduces the above impacts. In addition this paper presents the development of a portable device for implementing the above RTLS solution. The research makes use of Euclidean, standard deviation based and probabilistic algorithms. Data smoothening is done to reduce the multipath propagation issues. The different algorithm combinations are compared via their error cumulative distribution functions.

第 22 回アストロダイナミクスシンポジウム (2012 年 7 月 30-31 日. 宇宙航空研究開発機構宇宙科学研究所 (JAXA)(ISAS)), 相模原市, 神奈川県