Olfactory and/or visual cues for spatial navigation through ontogeny: olfactory cues enable the use of visual cues

This study analyzed the spatial memory capacities of rats in darkness with visual and/or olfactory cues through ontogeny. Tests were conducted with the homing board, where rats had to find the correct escape hole. Four age groups (24 days, 48 days, 3-6 months, and 12 months) were trained in 3 conditions: (a) 3 identical light cues; (b) 5 different olfactory cues; and (c) both types of cues, followed by removal of the olfactory cues. Results indicate that immature rats first take into account olfactory information but are unable to orient with only the help of discrete visual cues. Olfaction enables the use of visual information by 48-day-old rats. Visual information predominantly supports spatial cognition in adult and 12-month-old rats. Results point out cooperation between vision and olfaction for place navigation during ontogeny in rats.

Satellizing Galileo? Non-state Authority and Interoperability Standards in the European Global Navigation Satellite System

This paper explores the extent and limits of non-state authority in international affairs. While a number of studies have emphasised the role of state support and the ability of strategically situated actors to capture regulatory processes, they often fail to unpack the conditions under which this takes place. In order to probe the assumption that structural market power, backed by political support, equates regulatory capture, the article examines the interplay of political and economic considerations in the negotiations to establish worldwide interoperability standards needed for the development of Galileo as a genuinely European global navigation satellite system under civil control. It argues that industries supported and identified as strategic by public actors are more likely to capture standardisation processes than those with the largest market share expected to be created by the standards. This suggests that the influence of industries in space, air and maritime traffic control closely related to the militaro-industrial complex remains disproportionate in comparison to the prospective market of location-based services expected to vastly transform business practices, labour relations and many aspects of our daily life.

Development of place navigation in rats from weaning to puberty.

Young hooded rats were trained to escape onto a hidden platform after swimming in a pool of opaque water. Subjects 21, 28, 35, 42, and 64 days of age on the first training day were given 28 trials on 5 consecutive days. Half of the rats were required to localize the platform in relation to external room cues only ("place only" condition) and the other half were helped by the presence of a visible cue on the platform ("cue + place" condition). A deficiency in place navigation was observed in the 21- and 28-day groups; they showed slow escape and took circuitous routes more often than older rats. This deficiency was related to a poor spatial bias toward the training position when the subjects were allowed to swim for 30 s in the absence of the platform, at the end of the 28-trial training period (probe trial). The 35-day group showed adult-like learning ability in both training conditions, but failed to show searching behavior during the probe trial after having been trained in the presence of the proximal cue. Only rats older than 40 days showed typical adult behavior such as swimming directly toward the platform from any starting position and localized searching around the absent platform's position during the probe trial, no matter what the training conditions were. These results suggest that central nervous system structures responsible for place learning in the rat are functional from around 32 days of age, but fail to trigger searching behavior following cued training before the sixth week.

Dissociation of allocentric and egocentric orientation: Effect on hippocampal place cells and place navigation

Navigation by means of cognitive maps appears to require the hippocampus; hippocampal place cells (PCs) appear to store spatial memories because their discharge is confined to cell-specific places called firing fields (FFs). Experiments with rats manipulated idiothetic and landmark-related information to understand the relationship between PC activity and spatial rotation. Rotating a circular arena in the caused a discrepancy between these cuse. This discrepancy caused most FFs to disappear in both the arena and room reference frames. However, FFs persisted in the rotating arena frame when the discrepancy was reduced by darkness or by a card in the arena. The discrepancy was increased by "field clamping" the rat in a room-defined FF location by rotations that countered its locomotion. Most FFs disspared and reappeared an hour or more after the clamp. Place-avoidance experiments showed that navigation uses independent idiothetic and exteroceptive memories. Rats learned to avoid the unmarked footshock region within a circular arena. When acquired on the stable arena in the light, the location of the punishment was learned by using both room and idiothetic cues; extinction in the dark transferred to the following session in the light. If, however, extinction occured during rotation, only the arena-frame avoidance was extinguished in darkness; the room-defined location was avoided when the light were turned back on. Idiothetic memory of room-defined avoidance was not formed during rotation in light; regardless of rotation with a randomly dispersed pellet. The resulting behaviour alternated between random pellet searching and target-directed navigation, making it possible to examine PC correlates of these two classes of spatial behaviour. The independence of idiothetic and exteroceptive spatial memories and the disruption of PC firing during rotation suggest that PCs may not be necessary for spatial cognition; this idea can be tested by recording during place-avoidance and preference tasks.

Could a satellite-based navigation system (GPS) be used to assess the physical activity of individuals on earth?

OBJECTIVES: To test whether the Global Positioning System (GPS) could be potentially useful to assess the velocity of walking and running in humans. SUBJECT: A young man was equipped with a GPS receptor while walking running and cycling at various velocity on an athletic track. The speed of displacement assessed by GPS, was compared to that directly measured by chronometry (76 tests). RESULTS: In walking and running conditions (from 2-20 km/h) as well as cycling conditions (from 20-40 km/h), there was a significant relationship between the speed assessed by GPS and that actually measured (r = 0.99, P < 0.0001) with little bias in the prediction of velocity. The overall error of prediction (s.d. of difference) averaged +/-0.8 km/h. CONCLUSION: The GPS technique appears very promising for speed assessment although the relative accuracy at walking speed is still insufficient for research purposes. It may be improved by using differential GPS measurement.

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

A behavior-based scheme using reinforcement learning for autonomous underwater vehicles

This paper presents a hybrid behavior-based scheme using reinforcement learning for high-level control of autonomous underwater vehicles (AUVs). Two main features of the presented approach are hybrid behavior coordination and semi on-line neural-Q_learning (SONQL). Hybrid behavior coordination takes advantages of robustness and modularity in the competitive approach as well as efficient trajectories in the cooperative approach. SONQL, a new continuous approach of the Q_learning algorithm with a multilayer neural network is used to learn behavior state/action mapping online. Experimental results show the feasibility of the presented approach for AUVs

Policy gradient based Reinforcement Learning for real autonomous underwater cable tracking

This paper proposes a field application of a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot in cable tracking task. The learning system is characterized by using a direct policy search method for learning the internal state/action mapping. Policy only algorithms may suffer from long convergence times when dealing with real robotics. In order to speed up the process, the learning phase has been carried out in a simulated environment and, in a second step, the policy has been transferred and tested successfully on a real robot. Future steps plan to continue the learning process on-line while on the real robot while performing the mentioned task. We demonstrate its feasibility with real experiments on the underwater robot ICTINEU AUV

Autonomous underwater vehicle control using reinforcement learning policy search methods

Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task

Large-Area Photo-Mosaics Using Global Alignment and Navigation Data

Seafloor imagery is a rich source of data for the study of biological and geological processes. Among several applications, still images of the ocean floor can be used to build image composites referred to as photo-mosaics. Photo-mosaics provide a wide-area visual representation of the benthos, and enable applications as diverse as geological surveys, mapping and detection of temporal changes in the morphology of biodiversity. We present an approach for creating globally aligned photo-mosaics using 3D position estimates provided by navigation sensors available in deep water surveys. Without image registration, such navigation data does not provide enough accuracy to produce useful composite images. Results from a challenging data set of the Lucky Strike vent field at the Mid Atlantic Ridge are reported

Towards a real-time vision-based navigation system for a small-class UUV

This paper deals with the problem of navigation for an unmanned underwater vehicle (UUV) through image mosaicking. It represents a first step towards a real-time vision-based navigation system for a small-class low-cost UUV. We propose a navigation system composed by: (i) an image mosaicking module which provides velocity estimates; and (ii) an extended Kalman filter based on the hydrodynamic equation of motion, previously identified for this particular UUV. The obtained system is able to estimate the position and velocity of the robot. Moreover, it is able to deal with visual occlusions that usually appear when the sea bottom does not have enough visual features to solve the correspondence problem in a certain area of the trajectory

Probabilistic sonar scan matching for an AUV

This paper proposes MSISpIC, a probabilistic sonar scan matching algorithm for the localization of an autonomous underwater vehicle (AUV). The technique uses range scans gathered with a Mechanical Scanning Imaging Sonar (MSIS), the robot displacement estimated through dead-reckoning using a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method is an extension of the pIC algorithm. An extended Kalman filter (EKF) is used to estimate the robot-path during the scan in order to reference all the range and bearing measurements as well as their uncertainty to a scan fixed frame before registering. The major contribution consists of experimentally proving that probabilistic sonar scan matching techniques have the potential to improve the DVL-based navigation. The algorithm has been tested on an AUV guided along a 600 m path within an abandoned marina underwater environment with satisfactory results

A review of sensor fusion techniques for underwater vehicle navigation

This work provides a general description of the multi sensor data fusion concept, along with a new classification of currently used sensor fusion techniques for unmanned underwater vehicles (UUV). Unlike previous proposals that focus the classification on the sensors involved in the fusion, we propose a synthetic approach that is focused on the techniques involved in the fusion and their applications in UUV navigation. We believe that our approach is better oriented towards the development of sensor fusion systems, since a sensor fusion architecture should be first of all focused on its goals and then on the fused sensors