18568161
Analysis of locomotion of a planetary rover on a slope
For improvement of planetary rover locomotion, a new type of tracked vehicle was designed for planetary exploration based on the concept of reconfigurability. By applying the planetary wheel principle, the system can give output in different forms under various constraint conditions. As a reconfigurable module, the vehicle can be integrated into a larger system using two basic configurations. As a stand-alone rover, it has two moving modes. The whole design was analyzed by conducting dynamics simulations and experiments.
152660
Gaits-transferable CPG controller for a snake-like robot
With slim and legless body, particular ball articulation, and rhythmic locomotion, a nature snake adapted itself to many terrains under the control of a neuron system. Based on analyzing the locomotion mechanism, the main functional features of the motor system in snakes are specified in detail. Furthermore, a bidirectional cyclic inhibitory (BCI) CPG model is applied for the first time to imitate the pattern generation for the locomotion control of the snake-like robot, and its characteristics are discussed, particularly for the generation of three kinds of rhythmic locomotion. Moreover, we introduce the neuron network organized by the BCI-CPGs connected in line with unilateral excitation to switch automatically locomotion pattern of a snake-like robot under different commands from the higher level control neuron and present a necessary condition for the CPG neuron network to sustain a rhythmic output. The validity for the generation of different kinds of rhythmic locomotion modes by the CPG network are verified by the dynamic simulations and experiments. This research provided a new method to model the generation mechanism of the rhythmic pattern of the snake.
21075507
BP Networks Based Trajectory Planning and Inverse Kinematics of a Reconfigurable Mars Rover
The inverse kinematics of series manipulators presents an inherent complexity due to their various structures and kinematics constraints. To a novel reconfigurable Mars rover's arm, the inverse kinematics had been solved by numerical method combined with space geometry relations, but the complex calculating process can not be utilized in real-time control. In this paper, some actions in common use are programmed in the child rover, and the BP neural network was used to solve the inverse kinematics and trajectory planning. To a desired trajectory, some solutions by direct kinematics algorithms and geometry relations corresponding to the trajectory were used as the BP network's training data set, and the non-linear mapping from joint-variable space to operation-variable space was obtained with iterative training and learning method. The results show the output of training is consistent with the desired path, and the obtained reference trajectory is smooth.
206544153
Analysis of creeping locomotion of a snake robot on a slope
Biological snakes' diverse locomotion modes and physiology make them supremely adapted for environment. To realize these snakes' noticeable features, we have developed a snake-like robot that has no any forward direction driving force. To enlarge the environment-adaptable ability of our robot, in this study we discuss the creeping locomotion of our snake-like robot on a slope. A computer simulator is presented for analysis of the creeping locomotion of our snake-like robot on a slope, and the environment-adaptable body shape for the creeping locomotion of the snake-like robot on slope is also derived through this simulator.
10605413
Center-configuration selection technique for the reconfigurable modular robot
The reconfigurable modular robot has an enormous amount of configurations to adapt to various environments and tasks. It greatly increases the complexity of configuration research in that the possible configuration number of the reconfigurable modular robot grows exponentially with the increase of module number. Being the initial configuration or the basic configuration of the reconfigurable robot, the center-configuration plays a crucial role in system’s actual applications. In this paper, a novel center-configuration selection technique has been proposed for reconfigurable modular robots. Based on the similarities between configurations’ transformation and graph theory, configuration network has been applied in the modeling and analyzing of these configurations. Configuration adjacency matrix, reconfirmation cost matrix, and center-configuration coefficient have been defined for the configuration network correspondingly. Being similar to the center-location problem, the center configuration has been selected according to the largest center-configuration coefficient. As an example of the reconfigurable robotic system, AMOEBA-I, a three-module reconfigurable robot with nine configurations which was developed in Shenyang Institute of Automation (SIA), Chinese Academy of Sciences (CAS), has been introduced briefly. According to the numerical simulation result, the center-configuration coefficients for these nine configurations have been calculated and compared to validate this technique. Lastly, a center-configuration selection example is provided with consideration of the adjacent configurations. The center-configuration selection technique proposed in this paper is also available to other reconfigurable modular robots.
14083445
Network-based reconfiguration routes for a self-reconfigurable robot
This paper presents a network-based analysis approach for the reconfiguration problem of a self-reconfigurable robot. The self-reconfigurable modular robot named “AMOEBA-I” has nine kinds of non-isomorphic configurations that consist of a configuration network. Each configuration of the robot is defined to be a node in the weighted and directed configuration network. The transformation from one configuration to another is represented by a directed path with nonnegative weight. Graph theory is applied in the reconfiguration analysis, where reconfiguration route, reconfigurable matrix and route matrix are defined according to the topological information of these configurations. Algorithms in graph theory have been used in enumerating the available reconfiguration routes and deciding the best reconfiguration route. Numerical analysis and experimental simulation results prove the validity of the approach proposed in this paper. And it is potentially suitable for other self-reconfigurable robots’ configuration control and reconfiguration planning.
7090731
Anomaly Intrusion Detection Methods for Peer-to-Peer System
Peer-to-peer systems and applications are the hotspot of research of network applications. As peer-to-peer system has no central system and is deployed on an open network, new concerns regarding security have been raised. As an additional security measure, the intrusion detection system would help determine whether unauthorized users are attempting to access, have already accessed, or have compromised the network Intrusion detection, as the second line of defense, is an indispensable tool for highly survivable networks. In this paper two anomaly intrusion detection methods are proposed for peer-to-peer system. The main characters of the methods are that they can detect intrusion in real-time without any expert knowledge and attack signatures. One method uses hidden Markov model to check reflector DoS attacks, another based on adaptive resonance theory, which can learn the normal behavior with unsupervised method. The experimental P2P system is built on FreePastry 1.401 and JDK 1.5.0. The results have indicated that the methods can find DoS attacks immediately and find new intruders with low false alarm rate.
3472016
Detecting doubly compressed JPEG images by using Mode Based First Digit Features
In this paper, we utilize the probabilities of the first digits of quantized DCT (discrete cosine transform) coefficients from individual AC (alternate current) modes to detect doubly compressed JPEG images. Our proposed features, named by mode based first digit features (MBFDF), have been shown to outperform all previous methods on discriminating doubly compressed JPEG images from singly compressed JPEG images. Furthermore, combining the MBFDF with a multi-class classification strategy can be exploited to identify the quality factor in the primary JPEG compression, thus successfully revealing the double JPEG compression history of a given JPEG image.
1802579
Analysis and Improvement of An Iris Identification Algorithm
Iris recognition using complex valued 2D Gabor filters received a great success in broad applications. Such method encoded the iris phase information which was extracted according to the complex valued 2D filters' response. In this paper, we theoretically analyzed the complex-valued 2D Gabor filters. Based on analysis, we concluded that the real part of complex-valued 2D Gabor filter would reduce the whole system performance because it is not perfectly band passed filter. An improved algorithm then proposed to extract the phase information of iris image. The new method has more advantages such as lower false rate, much less space of codes and shorter time of encoding and matching. In order to reduce the disturbance of eyelashes, eyelids, specular reflections, or other noise, a matching template is designed by dilating the positions of them. Experimental results show that the latter method has an encouraging performance
16922329
A New Transmit Scheme Combining Beamforming with Space-Time Block Coding
In this paper, a new transmit scheme combining beamforming (BF) with space-time block coding (STBC) is proposed for correlated fading channels. Based on maximizing the output mean signal-to-noise ratio (SNR) at the receiver, the transmitter BF weight vectors are first derived. Then, utilizing the minimal bit error rate (BER) upper bound as the design criterion, a simple power allocation algorithm is developed. Next, the BER performance of the system with the proposed transmit scheme is analyzed by considering an M-QAM constellation. Finally, computer simulation results are given to verify the effectiveness of the proposed scheme.
62585345
An effective collision resolution mechanism for wireless LAN
Based on the current standardized IEEE 802.11 distributed coordination function (DCF) protocol, this paper proposes a new efficient collision resolution mechanism, called GDCF (gentle DCF). Our main motivation is based on the observation that 802.11 DCF decreases the contention window to the initial value after each success transmission, which essentially assumes that each successful transmission is an indication that the system is under low traffic loading. GDCF takes a more conservative measure by halving the contention window size after c consecutive successful transmissions. This "gentle" decrease lowers the collision probability, especially when the competing node number is large. We compute the optimal value for c, and the numerical results from both analysis and simulation demonstrate that GDCF significantly improve the performance of 802.11 DCF including throughput, fairness, and energy efficiency. In addition, GDCF is flexible for supporting priority access by selecting different values of c for different traffic types; it is fully compatible with the original 802.11 DCF, and simple to implement, as it does not requires changes in control message structure and access procedures in DCF.