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This paper presents a characterization study of the GLDT laser range finder (LRF). The LRF has long measuring range and high angular resolution. It is necessary to characterize the scanner before it is installed on our rescue robot which will work in unstructured indoor and outdoor environments. Besides examining the drift and how the distance affect the measurement accuracy, this paper also characterizes...
Effective far-range traversable region detection is a fundamental issue for mobile robots. However, the performance of traditional methods is limited as distance estimation of stereovision system is unreliable beyond 10–15m. In this paper, we proposed a far-range traversable region detection algorithm based on near-to-far self-supervised learning. In the algorithm, superpixel segmentation is employed...
This paper proposes a robust and precise localization system for mobile robots with the aid of Radio Frequency Identification (RFID) technology and the Markov Chain Monte Carlo (MCMC) optimization algorithm. By integrating the RFID module, RFID tags, a mobile robot and an off-board computer together, the localization system uses MCMC to analyze RFID signal information and get optimized mobile robot's...
Accurate and real-time traversable region detection is of great significance to the navigation of mobile robots. In Comparison with lasers and radars, stereo vision can provide richer information and thus has become increasingly popular in this field. In this paper, an efficient traversable region detection algorithm is proposed based on stereo vision by using u-v-disparity. In the algorithm, obstacle...
This article presented a localization algorithm of indoor mobile robot based on landmark. In order to navigate swiftly, one kind of landmark is designed, which is apt to recognize, convenient to extend. Because of noise error, the position of mobile robot calculated by single landmark is imprecise, so a method for localization of mobile robots was proposed by multiple landmarks. A mobile robot measures...
This paper presents a method for SLAM in Robot and Wireless Sensor Network (WSN) System using Bayes framework. A mobile robot equipped with sensor measuring the range to WSN nodes by Received Signal Strength Indicator (RSSI) can simultaneously localize itself as well as locate the sensor nodes of WSN. We adopted an algorithm based Rao-Blackwellized Particle Filter (RBPF) to integrate measurements...
In order to resolve the computational complexity for local map matching of hierarchical simultaneous localization and mapping (SLAM), a novel self-organizing fuzzy neural networks (SOFNN) based approach was proposed in this paper. The matching component for local maps in the hierarchical SLAM is realized by an SOFNN. A subset of signature elements included in a local map was chosen by a clustering...
How to make vision system work robustly under dynamic light conditions is still a challenging research focus in computer/robot vision community. In this paper, a novel camera parameters auto-adjusting technique based on image entropy is proposed. Firstly image entropy is defined and its relationship with camera parameters is verified by experiments. Then how to optimize the camera parameters based...
An improved particle filter algorithm is proposed for WSN-aided robot localization. This algorithm introduces node reliability and proposes its expression to realize information fusion among nodes. After having computed node reliability, sensor nodes with high localization, and take effect on updating particles according to their reliability. Furthermore, a novel simulation system for WSN-robot based...
A new laser scan matching method based on clustering is advanced. It takes the advantages of both non-iterative matching method and iterative matching method as well as increases the speed and the precision of matching. A method of map building based on laser scans using the matching method above is presented for mobile robots. The map building method matches two consecutive scans by using the feature...
Recognizing the FIFA ball without color classification is a significant ability for robocup middle size league soccer robots to play competition without the constraint of current color-coded environment. This paper describes a novel method to recognize the ball based on omni-directional vision system and perspective camera without color classification. Firstly the imaging character of the omni-directional...
This paper illustrates the reason why revisable data association is needed for the simultaneous localization and mapping (SLAM) of mobile robots, and an incremental SLAM algorithm with backtrack searching data association is presented. Our approach uses a tree model called correspondence tree (CT) to represent the solution space of the data association problem. CT is layered according to time steps...
One of the challenges of SLAM (simultaneous localization and mapping) for autonomous robots is the loop closing problem. In this paper, a decision-theoretic active loop closing approach is presented, which integrates the exploration planning with loop closing. In our approach, the active loop closing process is modeled as a multi-stage decision problem, and a frontier-based auxiliary topological map...
This paper presents a new algorithm for underwater geomagnetic-matching localization. The idea is rooted from image registration and workpiece localization problem. One essential elements of the new algorithm is an algorithm to solve transformation between two point sets. A related problem to this is fitting of two point sets (FTPS). In this paper, FTPS is first introduced and formulated to a least-squares...
This paper focuses on the reciprocity between data association and state estimation in the simultaneous localization and mapping (SLAM) problem for mobile robot, and an incremental SLAM algorithm with backtracking data association is presented. Our approach uses a tree model called correspondencetree (CT) to represent the solution space of the data association problem. CT is layered according to...
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