A Switching Controller System for a Wheeled Mobile Robot

A wheeled mobile mechanism with a passive and/or active linkage mechanism for rough terrain environment is developed and evaluated. The wheeled mobile mechanism which has high mobility in rough terrain needs sophisticated system to adapt various environments.We focus on the development of a switching controller system for wheeled mobile robots in rough terrain. This system consists of two sub-systems: an environment recognition system using link angles and an adaptive control system. In the environment recognition system, we introduce a Self-Organizing Map (SOM) for clustering link angles. In the adaptive controllers, we introduce neural networks to calculate the inverse model of the wheeled mobile robot.The environment recognition system can recognize the environment in which the robot travels, and the adjustable controllers are tuned by experimental results for each environment. The dual sub-system switching controller system is experimentally evaluated. The system recognizes its environment and adapts by switching the adjustable controllers. This system demonstrates superior performance to a well-tuned single PID controller.     

Simultaneous Optimization of Robot Structure and Control System Using Evolutionary Algorithm

The simultaneous optimization of a robot structure and control system to realize effective mobility in an outdoor environment is investigated. Recently, various wheeled mechanisms with passive and/or active linkages for outdoor environments have been developed and evaluated. We developed a mobile robot having six active wheels and passive linkage mechanisms, and experimentally verified its maneuverability in an indoor environment. However, there are various obstacles in outdoor environment and the travel ability of a robot thus depends on its mechanical structure and control system.We proposed a method of simultaneously optimizing mobile robot structure and control system using an evolutionary algorithm. Here, a gene expresses the parameters of the structure and control system. A simulated mobile robot and controller are based on these parameters and the behavior of the mobile robot is evaluated for three typical obstacles. From the evaluation results, new genes are created and evaluated repeatedly. The evaluation items are travel distance, travel time, energy consumption, control accuracy, and attitude of the robot.Effective outdoor travel is achieved around the 80th generation, after which, other parameters are optimized until the 300th generation. The optimized gene is able to pass through the three obstacles with low energy consumption, accurate control, and stable attitude.     

A Controller Design Method Based on a Neural Network for an Outdoor Mobile Robot

A wheeled mobile mechanism with a passive and/or active linkage mechanism for travel in rough terrain is developed and evaluated. In our previous research, we developed a switching controller system for wheeled mobile robots in rough terrain. This system consists of two sub-systems: an environment recognition system using a self-organizing map and an adjusted control system using a neural network. In this paper, we propose a new controller design method based on a neural network. The proposed method involves three kinds of controllers: an elementary controller, adjusted controllers, and simplified controllers. In the experiments, our proposed method results in less oscillatory motion in rough terrain and performs better than a well tuned PID controller does.     

Using insects to drive mobile robots — hybrid robots bridge the gap between biological and artificial systems

The use of mobile robots is an effective method of validating sensory–motor models of animals in a real environment. The well-identified insect sensory–motor systems have been the major targets for modeling. Furthermore, mobile robots implemented with such insect models attract engineers who aim to avail advantages from organisms. However, directly comparing the robots with real insects is still difficult, even if we successfully model the biological systems, because of the physical differences between them. We developed a hybrid robot to bridge the gap. This hybrid robot is an insect-controlled robot, in which a tethered male silkmoth (Bombyx mori) drives the robot in order to localize an odor source. This robot has the following three advantages: 1) from a biomimetic perspective, the robot enables us to evaluate the potential performance of future insect-mimetic robots; 2) from a biological perspective, the robot enables us to manipulate the closed-loop of an onboard insect for further understanding of its sensory–motor system; and 3) the robot enables comparison with insect models as a reference biological system. In this paper, we review the recent works regarding insect-controlled robots and discuss the significance for both engineering and biology.     

Abigaille-Ⅲ： A Versatile,Bioinspired Hexapod for Scaling Smooth Vertical Surfaces

This paper presents a novel, legged robot, Abigaille-Ⅲ, which is a hexapod actuated by 24 miniature gear motors. This robot uses dual-layer dry adhesives to climb smooth, vertical surfaces. Because dry adhesives are passive and stick to various surfaces, they have advantages over mechanisms such as suction, claws and magnets. The mechanical design and posture of Abigaille-Ⅲ were optimized to reduce pitchback forces during vertical climbing. The robot＇s electronics were designed around a Field Programmable Gate Array, producing a versatile computing architecture. The robot was reconfigured for vertical climbing with both 5 and 6 legs, and with 3 or 4 motors per leg, without changes to the electronic hardware. Abigaille-Ⅲ demonstrated dexterity through vertical climbing on uneven surfaces, and by transferring between horizontal and vertical sur- faces. In endurance tests, Abigaille-Ⅲ completed nearly 4 hours of continuous climbing and over 7 hours of loitering, showing that dry adhesive climbing systems can be used for extended missions.     

Self-Localization of an Omnidirectional Mobile Robot Based on an Optical Flow Sensor

An omnidirectional mobile robot has the advantage that three degrees of freedom of motion in a 2D plane can be set independently, and it can thus move in arbitrary directions while maintaining the same heading. Dead reckoning is often used for self-localization using onboard sensors in omnidirectional robots, by means of measuring wheel velocities from motor encoder data, as well as in car-like robots. However, omnidirectional mobile robots can easily slip because of the nature of omni-wheels with multiple free rollers, and dead reckoning will not work if even one wheel is not attached to the ground. An odometry method where the data is not affected by wheel slip must be introduced to acquire high quality self-location data for omnidirectional mobile robots. We describe a method to obtain robot ego-motion using camera images and optical flow calculation, i.e., where the camera is used as a velocity sensor. In this paper, a silicon retina vision camera is introduced as a mobile robot sensor, which has a good dynamic range under various lighting conditions. A Field-Programmable Gate Array (FPGA) optical flow circuit for the silicon retina is also developed to measure ego-motion of the mobile robot. The developed optical flow calculation system is introduced into a small omnidirectional mobile robot and evaluation experiments for the mobile robot ego-motion are carried out. In the experiments, the accuracy of self-location by the dead reckoning and optical flow methods are evaluated by comparison using motion capture. The results show that the correct position is obtained by the optical flow sensor rather than by dead reckoning.     

Evaluation by Expert Dancers of a Robot That Performs Partnered Stepping via Haptic Interaction

Our long-term goal is to enable a robot to engage in partner dance for use in rehabilitation therapy, assessment, diagnosis, and scientific investigations of two-person whole-body motor coordination. Partner dance has been shown to improve balance and gait in people with Parkinson''s disease and in older adults, which motivates our work. During partner dance, dance couples rely heavily on haptic interaction to convey motor intent such as speed and direction. In this paper, we investigate the potential for a wheeled mobile robot with a human-like upper-body to perform partnered stepping with people based on the forces applied to its end effectors. Blindfolded expert dancers (N=10) performed a forward/backward walking step to a recorded drum beat while holding the robot''s end effectors. We varied the admittance gain of the robot''s mobile base controller and the stiffness of the robot''s arms. The robot followed the participants with low lag (M=224, SD=194 ms) across all trials. High admittance gain and high arm stiffness conditions resulted in significantly improved performance with respect to subjective and objective measures. Biomechanical measures such as the human hand to human sternum distance, center-of-mass of leader to center-of-mass of follower (CoM-CoM) distance, and interaction forces correlated with the expert dancers'' subjective ratings of their interactions with the robot, which were internally consistent (Cronbach''s α=0.92). In response to a final questionnaire, 1/10 expert dancers strongly agreed, 5/10 agreed, and 1/10 disagreed with the statement "The robot was a good follower." 2/10 strongly agreed, 3/10 agreed, and 2/10 disagreed with the statement "The robot was fun to dance with." The remaining participants were neutral with respect to these two questions.     

Putting it together: the computational complexity of designing robot controllers and environments for distributed construction

Creating target structures through the coordinated efforts of teams of autonomous robots (possibly aided by specific features in their environments) is a very important problem in distributed robotics. Many specific instances of distributed robotic construction teams have been developed manually. An important issue is whether automated controller design algorithms can both quickly produce robot controllers and guarantee that teams using these controllers will build arbitrary requested target structures correctly; this task may also involve specifying features in the environment that can aid the construction process. In this paper, we give the first computational and parameterized complexity analyses of several problems associated with the design of robot controllers and environments for creating target structures. These problems use a simple finite-state robot controller model that moves in a non-continuous deterministic manner in a grid-based environment. Our goal is to establish whether algorithms exist that are both fast and correct for all inputs and if not, under which restrictions such algorithms are possible. We prove that none of these problems are efficiently solvable in general and remain so under a number of plausible restrictions on controllers, environments, and target structures. We also give the first restrictions relative to which these problems are efficiently solvable and discuss what theoretical solvability and unsolvability results derived relative to the problems examined here mean for real-world construction using robot teams.     

Full-state tracking control of a mobile robot using neural networks

In this paper a nonholonomic mobile robot with completely unknown dynamics is discussed. A mathematical model has been considered and an efficient neural network is developed, which ensures guaranteed tracking performance leading to stability of the system. The neural network assumes a single layer structure, by taking advantage of the robot regressor dynamics that expresses the highly nonlinear robot dynamics in a linear form in terms of the known and unknown robot dynamic parameters. No assumptions relating to the boundedness is placed on the unmodeled disturbances. It is capable of generating real-time smooth and continuous velocity control signals that drive the mobile robot to follow the desired trajectories. The proposed approach resolves speed jump problem existing in some previous tracking controllers. Further, this neural network does not require offline training procedures. Lyapunov theory has been used to prove system stability. The practicality and effectiveness of the proposed tracking controller are demonstrated by simulation and comparison results.     

Biomimetic Motion Control System Based on a CPG for an Amphibious Multi-Link Mobile Robot

Robots and robotics technologies are expected to provide new tools for inspection and manipulation, especially in extreme environments that are dangerous for human beings to access directly, such as underwater environments, volcanic areas, or nuclear power plants. Robots designed for such extreme environments should be sufficiently robust and strong to cope with disturbance and breakdowns. We focus on the movement of animals to realize robust robot systems. One approach is to mimic the nervous systems of animals. The central pattern generator of a nervous system has been shown to control motion patterns, such as walking, respiration and flapping. In this paper, a robot motion control system using a central pattern generator is proposed and applied to an amphibious multi-link mobile robot.     

From network-to-antibody robustness in a bio-inspired immune system

Behavioural robustness at antibody and immune network level is discussed. The robustness of the immune response that drives an autonomous mobile robot is examined with two computational experiments in the autonomous mobile robots trajectory generation context in unknown environments. The immune response is met based on the immune network metaphor for different low-level behaviours coordination. These behaviours are activated when a robot sense the appropriate conditions in the environment in relation to the network current state. Results are obtained over a case study in computer simulation as well as in laboratory experiments with a Khepera II microrobot. In this work, we develop a set of tests where such an immune response is externally perturbed at network or low-level behavioural modules to analyse the robust capacity of the system to unexpected perturbations. Emergence of robust behaviour and high-level immune response relates to the coupling between behavioural modules that are selectively engaged with the environment based on immune response. Experimental evidence leads discussions on a dynamical systems perspective of behavioural robustness in artificial immune systems that goes beyond the isolated immune network response.     

Persistence of Animal and Human Glycopeptide-Resistant Enterococci on Two Norwegian Poultry Farms Formerly Exposed to Avoparcin Is Associated with a Widespread Plasmid-Mediated vanA Element within a Polyclonal Enterococcus faecium Population

The evolutionary processes responsible for the long-term persistence of glycopeptide-resistant Enterococcus faecium (GREF) in nonselective environments were addressed by genetic analyses of E. faecium populations in animals and humans on two Norwegian poultry farms that were previously exposed to avoparcin. A total of 222 fecal GREF (n = 136) and glycopeptide-susceptible (n = 86) E. faecium (GSEF) isolates were obtained from farmers and poultry on three separate occasions in 1998 and 1999. Pulsed-field gel electrophoresis (PFGE) and plasmid DNA analyses discerned 22 GREF and 32 GSEF PFGE types within shifting polyclonal animal and human E. faecium populations and indicated the presence of transferable plasmid-mediated vanA resistance, respectively. Examples of dominant, persistent GREF PFGE types supported the notion that environmentally well-adapted GREF types may counteract the reversal of resistance. PFGE analyses, sequencing of the purK housekeeping gene, and partial typing of vanA-containing Tn1546 suggested a common animal and human reservoir of glycopeptide resistance. Inverse PCR amplification and sequence analyses targeting the right end of the Tn1546-plasmid junction fragment strongly indicated the presence of a common single Tn1546-plasmid-mediated element in 20 of 22 GREF PFGE types. This observation was further strengthened by vanY-vanZ hybridization analyses of plasmid DNAs as well as the finding of a physical linkage between Tn1546 and a putative postsegregation killing system for seven GREF PFGE types. In conclusion, our observations suggest that the molecular unit of persistence of glycopeptide resistance is a common mobile plasmid-mediated vanA-containing element within a polyclonal GREF population that changes over time. In addition, we propose that “plasmid addiction systems” may contribute to the persistence of GREF in nonselective environments.     

Mobile platform for motion capture of locomotion over long distances

Motion capture is usually performed on only a few steps of over-ground locomotion, limited by the finite sensing volume of most capture systems. This makes it difficult to evaluate walking over longer distances, or in a natural environment outside the laboratory. Here we show that motion capture may be performed relative to a mobile platform, such as a wheeled cart that is moved with the walking subject. To determine the person’s absolute displacement in space, the cart’s own motion must be localized. We present three localization methods and evaluate their performance. The first detects cart motion solely from the relative motion of the subject’s feet during walking. The others use sensed motion of the cart’s wheels to perform odometry, with and without an additional gyroscope to enhance sensitivity to turning about the vertical axis. We show that such methods are practical to implement, and with present-day sensors can yield accuracy of better than 1% over arbitrary distances.     

Protein Aggregation in E. coli?: Short Term and Long Term Effects of Nutrient Density

During exponential growth some cells of E. coli undergo senescence mediated by asymmetric segregation of damaged components, particularly protein aggregates. We showed previously that functional cell division asymmetry in E. coli was responsive to the nutritional environment. Short term exposure as well as long term selection in low calorie environments led to greater cell division symmetry and decreased frequency of senescent cells as compared to high calorie environments. We show here that long term selection in low nutrient environment decreased protein aggregation as revealed by fluorescence microscopy and proportion of insoluble proteins. Across selection lines protein aggregation was correlated significantly positively with the RNA content, presumably indicating metabolic rate. This suggests that the effects of caloric restriction on cell division symmetry and aging in E. coli may work via altered protein handling mechanisms. The demonstrable effects of long term selection on protein aggregation suggest that protein aggregation is an evolvable phenomenon rather than being a passive inevitable process. The aggregated proteins progressively disappeared on facing starvation indicating degradation and recycling demonstrating that protein aggregation is a reversible process in E. coli.     

Relationship of runs of homozygosity with adaptive and production traits in a paternal broiler line

Genomic regions under high selective pressure present specific runs of homozygosity (ROH), which provide valuable information on the genetic mechanisms underlying the adaptation to environment imposed challenges. In broiler chickens, the adaptation to conventional production systems in tropical environments lead the animals with favorable genotypes to be naturally selected, increasing the frequency of these alleles in the next generations. In this study, ~1400 chickens from a paternal broiler line were genotyped with the 600 K Affymetrix® Axiom® high-density (HD) genotyping array for estimation of linkage disequilibrium (LD), effective population size (N_e), inbreeding and ROH. The average LD between adjacent single nucleotide polymorphisms (SNPs) in all autosomes was 0.37, and the LD decay was higher in microchromosomes followed by intermediate and macrochromosomes. The N_e of the ancestral population was high and declined over time maintaining a sufficient number of animals to keep the inbreeding coefficient of this population at low levels. The ROH analysis revealed genomic regions that harbor genes associated with homeostasis maintenance and immune system mechanisms, which may have been selected in response to heat stress. Our results give a comprehensive insight into the relationship between shared ROH regions and putative regions related to survival and production traits in a paternal broiler line selected for over 20 years. These findings contribute to the understanding of the effects of environmental and artificial selection in shaping the distribution of functional variants in the chicken genome.     

Robotic and neuronal simulation of the hippocampus and rat navigation.

The properties of hippocampal place cells are reviewed, with particular attention to the nature of the internal and external signals that support their firing. A neuronal simulation of the firing of place cells in open-field environments of varying shape is presented. This simulation is coupled with an existing model of how place-cell firing can be used to drive navigation, and is tested by implementation as a miniature mobile robot. The sensors on the robot provide visual, odometric and short-range proximity data, which are combined to estimate the distance of the walls of the enclosure from the robot and the robot''s current heading direction. These inputs drive the hippocampal simulation, in which the robot''s location is represented as the firing of place cells. If a goal location is encountered, learning occurs in connections from the concurrently active place cells to a set of ''goal cells'', which guide subsequent navigation, allowing the robot to return to an unmarked location. The system shows good agreement with actual place-cell firing, and makes predictions regarding the firing of cells in the subiculum, the effect of blocking long-term synaptic changes, and the locus of search of rats after deformation of their environment.     

OmpA: Gating and dynamics via molecular dynamics simulations

Outer membrane proteins (OMPs) of Gram-negative bacteria have a variety of functions including passive transport, active transport, catalysis, pathogenesis and signal transduction. Whilst the structures of ∼ 25 OMPs are currently known, there is relatively little known about their dynamics in different environments. The outer membrane protein, OmpA from Escherichia coli has been studied extensively in different environments both experimentally and computationally, and thus provides an ideal test case for the study of the dynamics and environmental interactions of outer membrane proteins. We review molecular dynamics simulations of OmpA and its homologues in a variety of different environments and discuss possible mechanisms of pore gating. The transmembrane domain of E. coli OmpA shows subtle differences in dynamics and interactions between a detergent micelle and a lipid bilayer environment. Simulations of the crystallographic unit cell reveal a micelle-like network of detergent molecules interacting with the protein monomers. Simulation and modelling studies emphasise the role of an electrostatic-switch mechanism in the pore-gating mechanism. Simulation studies have been extended to comparative models of OmpA homologues from Pseudomonas aeruginosa (OprF) and Pasteurella multocida (PmOmpA), the latter model including the periplasmic C-terminal domain.     

Observations on the clypeasteroid Echinocyamus pusillus (O. F. Müller)

The tiny echinoid Echinocyamus pusillus (O. F. Müller) is equipped with specialized external structures that suit it for a wide variety of environments. Special features include the ability to burrow in sediments of fine sand to shell gravel and to climb vertically.Specimens dredged off the west coast of Scotland were observed in aquaria and with the SEM. E. pusillus is characterized by three kinds of spines, and by two of pedicellariae. In contrast to sand dollars, the spines play a passive rôle in the feeding and burrowing operation, probably retaining a defensive nature as in the regular urchins. It is the podia that are chiefly involved in climbing, burrowing, righting, and probably feeding. Surface ciliary currents transport particles, but not to the mouth; they may have a respiratory or cleansing function. Experimental animals did not burrow in either very fine or very coarse sand, probably because a certain relationship exists between particle weight and podia size.E. pusillus shares behavioural and structural characteristics with regular and irregular urchins. It is not a true sand dollar, but may illustrate an evolutionary stage towards such a form.