Molecular Lego (R): non-centrosymmetric alignment within interdigitating layers

(E)-N-Hexadecyl-4-[2-(4-octadecyloxynaphthyl) ethenyl] quinolinium bromide, which has a wide-bodied chromophore and terminal n-alkyl groups, adopts a U-shape when spread at the air-water interface but a stretched conformation when compressed to ca. 35 mN m(-1). The high-pressure phase has a narrow stability range prior to collapse but may be extended from 40 to 60 mN m(-1) by co-spreading the dye in a 1 : 1 ratio with docosanoic acid. The mixed Langmuir-Blodgett (LB) film has a monolayer thickness of 4.6 +/- 0.2 nm which decreases to 2.5 +/- 0.1 nm layer(-1) in the bulk, the reduction arising from an interdigitating layer arrangement, both top and bottom. It is the first example of LB-Lego(R) and, in addition, represents the only fully interdigitating structure with non-centrosymmetrically aligned chromophores. They are tilted 38 degrees from the substrate normal. The second-harmonic intensity increases quadratically with the number of layers, i.e. as I-(N)(2 omega) = (I(1)N2)-N-2 omega, with a second-order susceptibility of chi ((2))(zzz) = 30 pm V-1 at 1064 nm for refractive indices of n(omega) = 1.55 and n(2 omega) = 1.73, d = 2.5 nm layer(-1) and phi = 38 degrees. Angle resolved X-ray photoelectron spectra (XPS) of these films provide no evidence of the bromide counterion, which suggests that it is replaced by OH 2 or HCO3-, which occur naturally in the aqueous subphase, or C21H43COO- from the co-deposited fatty acid. This probably applies to all cationic dyes deposited by the LB technique.

Functional characterisation of an engineered multidomain human P450 E1 by molecular Lego

The human cytochrome P450s constitute an important family of monooxygenase enzymes that carry out essential roles in the metabolism of endogenous compounds and foreign chemicals. We present here results of a fusion between a human P450 enzyme and a bacterial reductase that for the first time is shown does not require the addition of lipids or detergents to achieve wild-type-like activities. The fusion enzyme, P450 2E1-BMR, contains the N-terminally modified residues 22-493 of the human P450 2E1 fused at the C-terminus to residues 473-1049 of the P450 BM3 reductase (BMR). The P450 2E1-BMR enzyme is active, self-sufficient and presents the typical marker activities of the native human P450 2E1: the hydroxylation of p-nitrophenol (K (M)=1.84 +/- 0.09 mM and k (cat) of 2.98 +/- 0.04 nmol of p-nitrocatechol formed per minute per nanomole of P450) and chlorzoxazone (K (M)=0.65 +/- 0.08 mM and k (cat) of 0.95 +/- 0.10 nmol of 6-hydroxychlorzoxazone formed per minute per nanomole of P450). A 3D model of human P450 2E1 was generated to rationalise the functional data and to allow an analysis of the surface potentials. The distribution of charges on the model of P450 2E1 compared with that of the FMN domain of BMR provides the ground for the understanding of the interaction between the fused domains. The results point the way to successfully engineer a variety of catalytically self-sufficient human P450 enzymes for drug metabolism studies in solution.

A global vision system for a robot soccer team

This paper describes the real time global vision system for the robot soccer team the RoboRoos. It has a highly optimised pipeline that includes thresholding, segmenting, colour normalising, object recognition and perspective and lens correction. It has a fast ‘paint’ colour calibration system that can calibrate in any face of the YUV or HSI cube. It also autonomously selects both an appropriate camera gain and colour gains robot regions across the field to achieve colour uniformity. Camera geometry calibration is performed automatically from selection of keypoints on the field. The system acheives a position accuracy of better than 15mm over a 4m × 5.5m field, and orientation accuracy to within 1°. It processes 614 × 480 pixels at 60Hz on a 2.0GHz Pentium 4 microprocessor.

Multi-robot control in highly dynamic, competitive environments

The control and coordination of multiple mobile robots is a challenging task; particularly in environments with multiple, rapidly moving obstacles and agents. This paper describes a robust approach to multi-robot control, where robustness is gained from competency at every layer of robot control. The layers are: (i) a central coordination system (MAPS), (ii) an action system (AES), (iii) a navigation module, and (iv) a low level dynamic motion control system. The multi-robot coordination system assigns each robot a role and a sub-goal. Each robot’s action execution system then assumes the assigned role and attempts to achieve the specified sub-goal. The robot’s navigation system directs the robot to specific goal locations while ensuring that the robot avoids any obstacles. The motion system maps the heading and speed information from the navigation system to force-constrained motion. This multi-robot system has been extensively tested and applied in the robot soccer domain using both centralized and distributed coordination.

Biologically inspired joint control for a humanoid robot

The GuRm is a 1.2m tall, 23 degree of freedom humanoid consuucted at the University of Queensland for research into humanoid robotics. The key challenge being addressed by the GuRw projcct is the development of appropriate learning strategies for control and coodinadon of the robot’s many joints. The development of learning strategies is Seen as a way to sidestep the inherent intricacy of modeling a multi-DOP biped robot. This paper outlines the approach taken to generate an appmpria*e control scheme for the joinis of the GuRoo. The paper demonsrrates the determination of local feedback control parameters using a genetic algorithm. The feedback loop is then augmented by a predictive modulator that learns a form of feed-fonward control to overcome the irregular loads experienced at each joint during the gait cycle. The predictive modulator is based on thc CMAC architecture. Results from tats on the GuRoo platform show that both systems provide improvements in stability and tracking of joint control.

A modified particle filter for simultaneous robot localization and landmark tracking in an indoor environment

This paper presents the implementation of a modified particle filter for vision-based simultaneous localization and mapping of an autonomous robot in a structured indoor environment. Through this method, artificial landmarks such as multi-coloured cylinders can be tracked with a camera mounted on the robot, and the position of the robot can be estimated at the same time. Experimental results in simulation and in real environments show that this approach has advantages over the extended Kalman filter with ambiguous data association and various levels of odometric noise.

UQ RoboRoos: Achieving power and agility in a small size robot

The UQ RoboRoos have been developed to participate in the RoboCup robot soccer small size league over several years. RoboCup 2001 saw a focus on the mechanical design of the RoboRoos, with the introduction of an omni-directional drive system and a high power kicker. The change in mechanical design had implications for the rest of the system particularly navigation and multi-robot planning. In addition, the overhead vision system was upgraded to improve reliability and robustness.

Hippocampal models for simultaneous localisation and mapping on an autonomous robot

To navigate successfully in a novel environment a robot needs to be able to Simultaneously Localize And Map (SLAM) its surroundings. The most successful solutions to this problem so far have involved probabilistic algorithms, but there has been much promising work involving systems based on the workings of part of the rodent brain known as the hippocampus. In this paper we present a biologically plausible system called RatSLAM that uses competitive attractor networks to carry out SLAM in a probabilistic manner. The system can effectively perform parameter self-calibration and SLAM in onedimension. Tests in two dimensional environments revealed the inability of the RatSLAM system to maintain multiple pose hypotheses in the face of ambiguous visual input. These results support recent rat experimentation that suggest current competitive attractor models are not a complete solution to the hippocampal modelling problem.