Fast DCT algorithm with fewer multiplication stages

A novel fast DCT scheme with reduced multiplication stages and fewer additions and multiplications is proposed. The proposed algorithm is structured so that most multiplications tend to be performed at the final stage, which reduces the propagation error that could occur in the fixed-point computation. Minimisation of the multiplication stages can further decrease the error     

Cue-based networking

In this paper we present a new approach called cue-based networking that uses hints or cues about the physical environment to optimize networked application behavior. We define the notion of cues and describe how cues can be obtained using wireless sensor networks as the underlying platform. We identify both the research and system challenges that need to be addressed to realize benefits of the approach under a target application of video delivery over IP networks. In the process, we identify key challenges of wireless sensor networks, namely timeliness and robustness. We design an adaptive algorithm that balances the tradeoff between them satisfying both timeliness and robustness requirements. Through an implementation of the video delivery application using the proposed algorithm in a real home environment, we highlight the practical benefits of the proposed approach.     

Experimental Verification of a Drift Controller for Autonomous Vehicle Tracking: a Circular Trajectory Using LQR Method

This study develops an autonomous vehicle control method that enables it to perform a drift maneuver which is an expert driving technique consisting of sliding the rear wheel intentionally for fast cornering. By developing an autonomous control algorithm for such an agile maneuver, the safety of the future autonomous vehicle on extreme conditions such as slippery road, will be increased. Drift equilibrium states are derived to find the suitable feedforward control input for the scale car to enter the drifting region. In addition, a feedback controller is designed based on the linear quadratic regulator method in order to track the circular trajectory and maintain drift equilibrium states. To validate the performance of the developed control algorithm a 1:10 scale car experimental platform is developed with on-board control and sensor system. The feasibility of the developed method for the autonomous vehicle is confirmed through both simulation and experiments following circular trajectories while maintaining the desired equilibrium states.

     

A robust lane recognition technique for vision-based navigation with a multiple clue-based filtration algorithm

This paper proposes a novel multiple clue-based filtration algorithm (MCFA), which is developed to detect lane markings on roads using camera vision images for autonomous mobile robot navigation. The main goal of the algorithm is the robust estimation of the relative position and angle of the lane in the image by using multiple clues based on different characteristics of the lane. In particular, robustness against environmental changes is enhanced greatly since a dynamic model of the lane, besides static features of the lane such as color, intensity, etc., is incorporated for reliable estimation. The efficiency of the algorithm is verified through mobile robot experiments under various extreme illumination conditions in outdoor environments. The increased robustness performance enables reliable closed-loop control of a mobile robot that operates in a variety of navigation-related missions.     

Adaptive nonlinear model predictive path-following control for a fixed-wing unmanned aerial vehicle

This paper presents an adaptive Nonlinear Model Predictive Control (NMPC) for the path-following control of a fixed-wing unmanned aerial vehicle (UAV). The objective is to minimize the mean and maximum errors between the reference path and the UAV. Navigating in a cluttered environment requires accurate tracking. However, linear controllers cannot provide good tracking performance due to nonlinearities that arise in the system dynamics and physical limitations such as actuator saturation and state constraints. NMPC provides an alternative since it can combine multiple objectives and constraints, which minimize the objective function. However, it is difficult to decide appropriate control horizon since the path-following performance depends on the profile of the path. Therefore, a fixed-horizon NMPC cannot guarantee accurate tracking performance. An adaptive NMPC that varies the control horizon according to the path curvature profile for tight tracking is proposed in this paper. Simulation results show that the proposed adaptive NMPC controller can follow the path more accurately than a conventional, fixed-horizon NMPC.     

Reversible Switching Phenomenon in Diarylethene Molecular Devices with Reduced Graphene Oxide Electrodes on Flexible Substrates

Photoswitching molecular electronic devices with reduced graphene oxide (rGO) top electrodes on flexible substrates are fabricated and characterized. It has been reported previously that diarylethene molecular devices with poly‐(3,4‐ethylenedioxythiophene) stabilized with poly‐(4‐styrenesulfonic acid)/Au top electrodes can hold two stable electrical conductance states when the devices are exposed to UV or visible light during device fabrication. However, those devices fail to show the reversible switching phenomenon in response to illumination after device fabrication. By employing conducting and transparent rGO top electrodes, it is demonstrated that the diarylethene molecular devices show a reversible switching phenomenon, i.e., the fabricated devices change their conductance state in response to the alternating illumination with UV and visible light. Furthermore, the molecular devices with rGO top electrodes also exhibit good longtime stability and reliable electrical characteristics when subjected to various mechanical stresses (bending radius down to 5 mm and bending cycle over 10⁴).     

Simultaneous braking and steering control method based on nonlinear model predictive control for emergency driving support

Autonomous emergency braking (AEB) has drawn a lot of attention as an active safety system preventing rear-end collision avoidance when the relative speed between vehicles is slow. To increase the operation range of current AEB system, this paper suggests a collision avoidance strategy using steering and braking simultaneously with nonlinear model predictive control (NMPC) method. The NMPC predicts the vehicle’s future trajectory with its open-loop dynamics and calculates the error between the predicted and the desired paths. Then NMPC calculates the control inputs such as the wheel steering angle and vehicle acceleration by optimizing the cost function over future receding horizon with predetermined constraints. In this paper, constraints on the wheel steering angle is proposed in consideration of vehicle’s predicted lateral acceleration, which should be smaller than the threshold in order to maintain lateral vehicle’s stability. To verify the performance of the proposed strategy, two simulation scenarios were tested in MATLAB and CarSim simulation environments.

     

Mobile hosts participating in peer-to-peer data networks: challenges and solutions

Peer-to-peer (P2P) data networks dominate Internet traffic, accounting for over 60% of the overall traffic in a recent study. In this work, we study the problems that arise when mobile hosts participate in P2P networks. We primarily focus on the performance issues as experienced by the mobile host, but also study the impact on other fixed peers. Using BitTorrent as a key example, we identify several unique problems that arise due to the design aspects of P2P networks being incompatible with typical characteristics of wireless and mobile environments. Using the insights gained through our study, we present a wireless P2P client application that is backward compatible with existing fixed-peer client applications, but when used on mobile hosts can provide significant performance improvements.     

VoIP over Wi-Fi Networks: Performance Analysis and Acceleration Algorithms

The expected VoIP call capacity in a one hop IEEE 802.11b network with G.711 voice codec is about 85 simultaneous calls, but the actual observed capacity is only 5 calls even at the highest data rate and under zero loss conditions. In this paper we analyze the reasons behind this inferior performance of VoIP traffic. We also present algorithms at the medium access control layer to improve the observed call capacity. Using ns-2 based simulations, we evaluate the algorithms and show that performance improvements of more than 300% can be achieved. Finally, using a testbed implementation of one of the proposed algorithms, we show its feasibilty in real world VoIP implementations. An earlier version of this paper was published in the IEEE Conference on Broadband Communications, Networks, and Systems (BroadNets) 2007 [1]. This work was supported in part by the National Science Foundation under grants CNS-0519733 and CNS-0721296, and the Georgia Tech Broadband Institute. Yeonsik Jeong was also supported under the Korea Research Foundation Grant KRF-2005-214-D00362 funded by the Korean Government (MOEHRD). This work was performed when Y. Jeong was a research scientist in the GNAN research group at Georgia Institute of Technology.     

Interference mitigation in wireless sensor networks using dual heterogeneous radios

Scalability is one of the most important features that future wireless sensor networks (WSNs) should provide, and clustering is widely considered as a viable approach for high scalability. In the cluster-based architecture, the cluster heads play a key role in relaying messages between the sensor nodes and the sink. While the cluster heads are involved in both intra-cluster and inter-cluster communication, the latter typically requires transmission over much longer distance than the former. In this paper, we consider a scenario in which each cluster head is equipped with dual radios: IEEE 802.15.4 and IEEE 802.11 for intra-cluster and inter-cluster communication, respectively. IEEE 802.11 links between the cluster heads and the sink provide a high capacity backbone for large-scale WSNs. IEEE 802.15.4 and IEEE 802.11 share a lot of similarities including CSMA/CA MAC. Their operating spectrum also overlaps at the 2.4 GHz ISM band, and this may cause interference. We first experimentally measure how severe the interference can be, when two radios are concurrently used in a WSN. We, then, propose an interference mitigation solution which relies on adaptive aggregation of packets and adaptive transmission scheduling. Through prototyping and experimental evaluation, we show that the proposed scheme significantly reduces the interferences between the two types of radios.