Study of Indoor Visual SLAM System for Semi-autonomous Robot Platform

This study propose the use of heterogeneous visual landmarks, points and line segments, to achieve effective cooperation in indoor SLAM environments. In order to achieve un-delayed initialization required by the bearing-only observations, the well-known inverse-depth parameterization is adopted to estimate 3D points. Similarly, to estimate 3D line segments, we present a novel parameterization based on anchored Plücker coordinates, to which extensible endpoints are added

Animate Orientation Based on Visual Landmarks and Scene Recognition

A biologically-inspired approach to robot route following is presented. The ant of the genus Formica rufa (a red forest ant) is used as a model species. These ants actively use collective foraging, unlike many other ant species. The scout ant remembers the route to food and can transmit information about the food location to foraging ants. Foragers can independently reach this place using this data and return home. The basis of the proposed method is the memorization the way by visual landmarks and fuzzy control. The animate path description model consists of a sequence of scenes and includes compass to account for the direction. The behavior of the animate-scout is implemented using an algorithm that simulates the foraging behavior of ants. The animate-forager performs actions to reproduce the route, applying the developed set of rules. The forager behavior is based on the same principles as that of a scout. But the scout remembers the scenes, and the forager recognizes and compares the visible scene and the scene from the route description. The actions of animates are presented in the form of elementary behavioral procedures. Each behavioral procedure is implemented using a finite state machine. The experiments for solving the foraging problem were carried out using a modeling system based on the ROS framework. The simulation results confirm the effectiveness of the proposed method. The method does not require large computing power and advanced sensory capabilities from the robot. It can also be used in reconnaissance and patrol tasks.

Write Clear Research Explanations

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GPS-Free, Error Tolerant Path Planning for Swarms of Micro Aerial Vehicles with Quality Amplification

We present an error tolerant path planning algorithm for Micro Aerial Vehicle (MAV) swarms. We assume navigation without GPS-like techniques. The MAVs find their path using sensors and cameras, identifying and following a series of visual landmarks. The visual landmarks lead the MAVs towards their destination. MAVs are assumed to be unaware of the terrain and locations of the landmarks. They hold a priori information about landmarks, whose interpretation is prone to errors. Errors are of two types, recognition or advice. Recognition errors follow from misinterpretation of sensed data or a priori information, or confusion of objects, e.g., due to faulty sensors. Advice errors are consequences of outdated or wrong information about landmarks, e.g., due to weather conditions. Our path planning algorithm is cooperative. MAVs communicate and exchange information wirelessly, to minimize the number of recognition and advice errors. Hence, the quality of the navigation decision process is amplified. Our solution successfully achieves an adaptive error tolerant navigation system. Quality amplification is parameterized with respect to the number of MAVs. We validate our approach with theoretical proofs and numeric simulations.

Investigating drivers’ geospatial abilities in unfamiliar environments

The prominence of landmarks in aiding pedestrian navigation has been highlighted in various studies; people rely strongly on visual landmarks, especially when navigating in unfamiliar environments. The paper describes the design and implementation of a study for assessing drivers’ spatial abilities, when navigating in an unfamiliar environment. Two types of route directions based on references to either landmarks or street names were given to two groups of participants. Three geospatial learning tasks are used to evaluate these abilities: map sketching, distance, and direction estimation. The findings showed that landmark-based route instructions help drivers develop a better cognitive map of the route. On the other hand, instructions either based on landmarks or on street information do not have an effect on distance or direction estimates. Nonetheless, qualitative analysis of directions and distances estimations gave interesting results. Findings associated with self-assessment of environmental spatial abilities using the Santa Barbara Sense of Direction Scale (SBSOD) seem to support prediction of at least one of the drivers’ abilities among those assessed in this study.

Landmark-Centered Coding in Frontal Cortex Visual Responses

Visual landmarks influence spatial cognition, navigation and goal-directed behavior, but their influence on visual coding for action is poorly understood. Here, we tested landmark influence on prefrontal visual responses by recording from 568 neurons in the frontal (FEF) and supplementary (SEF) eye fields of rhesus macaques. The response field (the area of visual space that modulates activity) for each neuron was tested in the presence of a landmark placed at one of four configurations. We then fit the spatially tuned response fields against a spatial coordinate continuum between gaze- and landmark-centered models. When response fields were fit separately for each target-landmark configuration, the best fits shifted (mean 37% / 40%) toward landmark-centered coding in FEF / SEF respectively, confirming a configuration-dependent intermediate coding scheme. Overall, these data show that external landmarks influence prefrontal visual responses, possibly helping to stabilize movement goals in the presence of noisy internal egocentric signals.

Herders and Pioneers: The Role of Pastoralism in the Neolithization of the Amblés Valley (Ávila, Central Iberia)

In recent years, the notion of landscape learning has been the object of increasing attention when discussing the neolithization of Europe. The landscape learning model stresses the necessity of gathering environmental information about a previously unfamiliar region. Therefore, it is particularly relevant in cases where the beginning of a farming economy is better explained in relation to the movements of peoples (colonization), rather than to the adoption of crops and livestock by pre-existing hunters and gatherers (acculturation). Unlike other Iberian regions, where the adoption of agriculture runs parallel to that of animal husbandry, the available data on the neolithization process of the Sierra de Gredos mountain range seem to suggest that raising livestock may have preceded plant cultivation. Based on an interdisciplinary and multi-proxy approach, this paper explores the idea that the adoption of a food-producing economy in the Amblés Valley (Ávila, Central Iberia) may have been connected with pastoralism. In this context, landscape learning provides a model for analyzing how Early Neolithic herders in their seasonal movements were capable of wayfinding by memorizing spatial features that functioned as visual landmarks.

Landmark-Centered Coding in Frontal Cortex Visual Responses

SummaryVisual landmarks influence spatial cognition [1–3], navigation [4,5] and goal-directed behavior [6–8], but their influence on visual coding in sensorimotor systems is poorly understood [6,9–11]. We hypothesized that visual responses in frontal cortex control gaze areas encode potential targets in an intermediate gaze-centered / landmark-centered reference frame that might depend on specific target-landmark configurations rather than a global mechanism. We tested this hypothesis by recording neural activity in the frontal eye fields (FEF) and supplementary eye fields (SEF) while head-unrestrained macaques engaged in a memory-delay gaze task. Visual response fields (the area of visual space where targets modulate activity) were tested for each neuron in the presence of a background landmark placed at one of four oblique configurations relative to the target stimulus. 102 of 312 FEF and 43 of 256 SEF neurons showed spatially tuned response fields in this task. We then fit these data against a mathematical continuum between a gaze-centered model and a landmark-centered model. When we pooled data across the entire dataset for each neuron, our response field fits did not deviate significantly from the gaze-centered model. However, when we fit response fields separately for each target-landmark configuration, the best fits shifted (mean 37% / 40%) toward landmark-centered coding in FEF / SEF respectively. This confirmed an intermediate gaze / landmark-centered mechanism dependent on local (configuration-dependent) interactions. Overall, these data show that external landmarks influence prefrontal visual responses, likely helping to stabilize gaze goals in the presence of variable eye and head orientations.HighlightsPrefrontal visual responses recorded in the presence of visual landmarksResponse fields showed intermediate gaze / landmark-centered organizationThis influence depended on specific target-landmark configurations