José M. Claver

Bidirectional Transport Protocol for Teleoperated Robots

This paper describes a new Internet transport protocol applied to teleoperated tasks. This protocol, called bidirectional transport protocol (BTP), has demonstrated reliable performance regarding time spent for packet transmission. This protocol provides a novel congestion control technique which enhances application and transport layer performance. Internet still has some limitations, such as variable jitter, bandwidth, or congestion. New techniques have to be looked into so as to enable proper bilateral teleoperation. Most research to date focuses on the application layer such as control techniques (e.g., passivity) or predictive displays. Only a few studies are devoted to the transport layer or communication protocols. A testbed based on master-slave architecture has been used for testing BTP versus user datagram protocol (UDP). Transmission control protocol flows also coexist with the transmitted teleoperation data. Results show that the proposed protocol significantly enhances the UDP approach by achieving a minimum round trip time and interarrival time in relation to the available bandwidth of the network.

Remote Programming of Network Robots Within the UJI Industrial Robotics Telelaboratory: FPGA Vision and SNRP Network Protocol

This paper presents the UJI Industrial Robotics Telelaboratory, which lets Ph.D. and Masters degree students perform robotics and computer vision tele-experiments. By using this system, students are able to program experiments remotely via the Web, in order to combine the use of a field-programmable gate array (FPGA) to provide real-time vision processing, a conveyor belt, and a Motoman industrial manipulator. This paper introduces the novel SNRP protocol (i.e., Simple Network Robot Protocol), which permits the integration of network robots and sensors within an e-learning platform in a simple and reliable manner. As long as the students are able to interact remotely with a real robotic scenario, this system helps students very much to learn robotics control techniques like visual servoing control, vision for industrial applications, and robotics manipulation. The various components of the system are connected via a 100BaseT Ethernet network and follow the SNRP protocol, which grants simple access to generic networked devices using enhanced HTTP-based connections. Moreover, the whole telelaboratory is connected to the Internet through a router that permits the user to control the networked devices according to security constraints. The SNRP architecture is compared with a Common Object Request Broker Architecture-based approach, which was used in a previous telelaboratory. This paper describes two principle contributions: the design of a novel SNRP network architecture for the intercommunication of robots and sensors within an e-learning telelaboratory and the integration of a programmable FPGA vision system, which allows students to learn not only robotic techniques but also the design of high-performance circuits for industrial vision applications.

Reducing complexity in H.264/AVC motion estimation by using a GPU

H.264/AVC applies a complex mode decision technique that has high computational complexity in order to reduce the temporal redundancies of video sequences. Several algorithms have been proposed in the literature in recent years with the aim of accelerating this part of the encoding process. Recently, with the emergence of many-core processors or accelerators, a new approach can be adopted for reducing the complexity of the H.264/AVC encoding algorithm. This paper focuses on reducing the inter prediction complexity adopted in H.264/AVC and proposes a GPU-based implementation using CUDA. Experimental results show that the proposed approach reduces the complexity by as much as 99% (100x of speedup) while maintaining the coding efficiency.

Accelerating H.264 inter prediction in a GPU by using CUDA

H.264/AVC defines a very efficient algorithm for the inter prediction but it takes too much time. With the emergence of general purpose graphics processing units (GPGPU), a new door has been opened to support this video algorithm into these small processing units. In this paper, a forward step is developed towards an implementation of the H.264/AVC inter prediction algorithm into a GPU using compute unified device architecture (CUDA). The results show a negligible rate distortion drop with a time reduction on average up to 93.6%.

Efficient Transport Protocol for Networked Haptics Applications

The performance of haptic application is highly sensitive to communication delays and losses of data. It implies several constraints in developing networked haptic applications. This paper describes a new internet protocol called Efficient Transport Protocol (ETP), which aims at developing distributed interactive applications. TCP and UDP are transport protocols commonly used in any kind of networked communication, but they are not focused on real time application. This new protocol is focused on reducing roundtrip time (RTT) and interpacket gap (IPG). ETP is, therefore, optimized for interactive applications which are based on processes that are continuously exchanging data. ETP protocol is based on a state machine that decides the best strategies for optimizing RTT and IPG. Experiments have been carried out in order to compare this new protocol and UDP.

RF-Based Location Using Interpolation Functions to Reduce Fingerprint Mapping.

Indoor RF-based localization using fingerprint mapping requires an initial training step, which represents a time consuming process. This location methodology needs a database conformed with RSSI (Radio Signal Strength Indicator) measures from the communication transceivers taken at specific locations within the localization area. But, the real world localization environment is dynamic and it is necessary to rebuild the fingerprint database when some environmental changes are made. This paper explores the use of different interpolation functions to complete the fingerprint mapping needed to achieve the sought accuracy, thereby reducing the effort in the training step. Also, different distributions of test maps and reference points have been evaluated, showing the validity of this proposal and necessary trade-offs. Results reported show that the same or similar localization accuracy can be achieved even when only 50% of the initial fingerprint reference points are taken.

End-to-end congestion control protocols for remote programming of robots, using heterogeneous networks: A comparative analysis

There are many interesting aspects of Internet Telerobotics within the network robotics context, such as variable bandwidth and time-delays. Some of these aspects have been treated in the literature from the control point of view. Moreover, only a little work is related to the way Internet protocols can help to minimize the effect of delay and bandwidth fluctuation on network robotics. In this paper, we present the capabilities of TCP, UDP, TCP Las Vegas, TEAR, and Trinomial protocols, when performing a remote experiment within a network robotics application, the UJI Industrial Telelaboratory. Comparative analysis is presented through simulations within the NS2 platform. Results show how these protocols perform in two significant situations within the network robotics context, using heterogeneous wired networks: (1) an asymmetric network when controlling the system through a ADSL connection, and (2) a symmetric network using the system on Campus. Conclusions show a set of characteristics the authors of this paper consider very important when designing an End-to-End Congestion Control transport protocol for Internet Telerobotics.

A fast GPU-based motion estimation algorithm for H.264/AVC

H.264/AVC is the most recent predictive video compression standard to outperform other existing video coding standards by means of higher computational complexity. In recent years, heterogeneous computing has emerged as a cost-efficient solution for high-performance computing. In the literature, several algorithms have been proposed to accelerate video compression, but so far there have not been many solutions that deal with video codecs using heterogeneous systems. This paper proposes an algorithm to perform H.264/AVC inter prediction. The proposed algorithm performs the motion estimation, both with full-pixel and sub-pixel accuracy, using CUDA to assist the CPU, obtaining remarkable time reductions while maintaining rate-distortion performance.

Conquer the Net: An educational computer game to learn the basic configuration of networking components

Advanced networking equipment is relatively expensive and student access to it is usually limited to scheduled times at computer laboratories within the university premises. Hence, it is important to make the most effective use of the time assigned and minimize the time that students spend in activities which can be performed outside the laboratory sessions. Familiarizing with the basic configuration commands is one such activity. We have developed a computer game to allow students to learn these in a motivating and pleasant environment. This game has been designed so that rules are easily learned and both cooperative and competitive learning are promoted.

Individual Variability and Average Reliability in Parallel Networks of Heterogeneous Biological and Artificial Nanostructures

We simulate the collective electrical response of heterogeneous ensembles of biological and artificial nanostructures whose individual threshold potentials show a significant variability. This problem is of current interest because nanotechnology is bound to produce nanostructures with a significant experimental variability in their individual physical properties. This diversity is also present in biological systems that are however able to process information efficiently. The nanostructures considered are the ion channels of biological membranes, nanowire field-effect transistors, and metallic nanoparticle-based single electron transistors. These systems are simulated with canonical models that incorporate the basic threshold characteristics observed in the respective experimental current-voltage curves. In each case, the different shape, size, and charge distributions of the nanostructures result in statistical distributions for the individual threshold potentials, characterized by experimental average and width distribution values, rather than in identical replicates of the same unit. Despite the significant variability, the simulations suggest that useful average responses can still be achieved with summing networks of heterogeneous nanostructures because the collective behavior may compensate for individual failures and variability. Since threshold potential systems are commonplace in biology, the results obtained are also significant for understanding the role of diversity in biologically inspired networks.