08291 Abstracts Collection -- Statistical and Geometrical Approaches to Visual Motion Analysis

From 13.07.2008 to 18.07.2008, the Dagstuhl Seminar 08291 ``Statistical and Geometrical Approaches to Visual Motion Analysis\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general

Biologically inspired, self organizing communication networks.

PhDThe problem of energy-efficient, reliable, accurate and self-organized target tracking in Wireless Sensor Networks (WSNs) is considered for sensor nodes with limited physical resources and abrupt manoeuvring mobile targets. A biologically inspired, adaptive multi-sensor scheme is proposed for collaborative Single Target Tracking (STT) and Multi-Target Tracking (MTT). Behavioural data obtained while tracking the targets including the targets’ previous locations is recorded as metadata to compute the target sampling interval, target importance and local monitoring interval so that tracking continuity and energy-efficiency are improved. The subsequent sensor groups that track the targets are selected proactively according to the information associated with the predicted target location probability such that the overall tracking performance is optimized or nearly-optimized. One sensor node from each of the selected groups is elected as a main node for management operations so that energy efficiency and load balancing are improved. A decision algorithm is proposed to allow the “conflict” nodes that are located in the sensing areas of more than one target at the same time to decide their preferred target according to the target importance and the distance to the target. A tracking recovery mechanism is developed to provide the tracking reliability in the event of target loss. The problem of task mapping and scheduling in WSNs is also considered. A Biological Independent Task Allocation (BITA) algorithm and a Biological Task Mapping and Scheduling (BTMS) algorithm are developed to execute an application using a group of sensor nodes. BITA, BTMS and the functional specialization of the sensor groups in target tracking are all inspired from biological behaviours of differentiation in zygote formation. Simulation results show that compared with other well-known schemes, the proposed tracking, task mapping and scheduling schemes can provide a significant improvement in energy-efficiency and computational time, whilst maintaining acceptable accuracy and seamless tracking, even with abrupt manoeuvring targets.Queen Mary university of London full Scholarshi

Bio-Inspired Autonomous Learning Algorithm With Application to Mobile Robot Obstacle Avoidance

Spiking Neural Networks (SNNs) are often considered the third generation of Artificial Neural Networks (ANNs), owing to their high information processing capability and the accurate simulation of biological neural network behaviors. Though the research for SNNs has been quite active in recent years, there are still some challenges to applying SNNs to various potential applications, especially for robot control. In this study, a biologically inspired autonomous learning algorithm based on reward modulated spike-timing-dependent plasticity is proposed, where a novel rewarding generation mechanism is used to generate the reward signals for both learning and decision-making processes. The proposed learning algorithm is evaluated by a mobile robot obstacle avoidance task and experimental results show that the mobile robot with the proposed algorithm exhibits a good learning ability. The robot can successfully avoid obstacles in the environment after some learning trials. This provides an alternative method to design and apply the bio-inspired robot with autonomous learning capability in the typical robotic task scenario

Stroboscopic vision when interacting with multiple moving objects: Perturbation is not the same as elimination

Motivated by recent findings of improved perceptual processing and perceptual-motor skill following stroboscopic vision training, the current study examined the performance and acquisition effects of stroboscopic vision methods that afford a different visual experience. In Experiment 1, we conducted a within-subject design study to examine performance of a multiple object tracking (MOT) task in different stroboscopic vision conditions (Nike Vapor Strobe®, PLATO visual occlusion, intermittent display presentation) operating at 5.6, 3.2 or 1.8Hz. We found that participants maintained MOT performance in the Vapor Strobe condition irrespective of strobe rate. However, MOT performance deteriorated as strobe rate was reduced in the other two stroboscopic vision conditions. Moreover, at the lowest strobe rate (1.8Hz) there was an increase in probe reaction time, thus indicating an increased attentional demand due to the stroboscopic vision. In Experiment 2, we conducted a mixed design study to examine if practice in different stroboscopic vision conditions (Nike Vapor Strobe®, PLATO visual occlusion) influenced acquisition of a novel precision-aiming task (i.e., multiple object avoidance (MOA) task) compared to a normal vision group. Participants in the PLATO visual occlusion group exhibited worse performance during practice than the Vapor Strobe and normal vision groups. At post-test, the Vapor Strobe group demonstrated greater success and reduced end-point error than the normal vision and PLATO groups. We interpret these findings as showing that both an intermittent perturbation (Nike Vapor Strobe®) and elimination (PLATO visual occlusion, intermittent display presentation) of visual motion and form are more attention demanding (Experiment 1), however the intermittent perturbation, but not elimination, of visual motion and form can facilitate acquisition of perceptual-motor skill (Experiment 2) in situations where it is necessary to maintain and update a spatio-temporal representation of multiple moving objects

Path Planning and Energy Efficiency of Heterogeneous Mobile Robots Using Cuckoo–Beetle Swarm Search Algorithms with Applications in UGV Obstacle Avoidance

In this paper, a new meta-heuristic path planning algorithm, the cuckoo–beetle swarm search (CBSS) algorithm, is introduced to solve the path planning problems of heterogeneous mobile robots. Traditional meta-heuristic algorithms, e.g., genetic algorithms (GA), particle swarm search (PSO), beetle swarm optimization (BSO), and cuckoo search (CS), have problems such as the tenancy to become trapped in local minima because of premature convergence and a weakness in global search capability in path planning. Note that the CBSS algorithm imitates the biological habits of cuckoo and beetle herds and thus has good robustness and global optimization ability. In addition, computer simulations verify the accuracy, search speed, energy efficiency and stability of the CBSS algorithm. The results of the real-world experiment prove that the proposed CBSS algorithm is much better than its counterparts. Finally, the CBSS algorithm is applied to 2D path planning and 3D path planning in heterogeneous mobile robots. In contrast to its counterparts, the CBSS algorithm is guaranteed to find the shortest global optimal path in different sizes and types of maps

Aerospace medicine and biology. A continuing bibliography with indexes, supplement 206, May 1980

This bibliography lists 169 reports, articles, and other documents introduced into the NASA scientific and technical information system in April 1980

The design of an autonomous maritime navigation system for unmanned surface vehicles

This paper presents the development of an autonomous maritime navigation system for unmanned surface vehicles (USVs). In the autonomous system various maritime navigational devices are connected to obtain necessary navigational information but with uncertainties. To improve signal accuracy as well as robustness, a novel multi-sensor data fusion algorithm is proposed and developed. Then, a new predictive path planning algorithm is employed to provide an advisory collision-free trajectory. Practical trials and computer based simulations are carried out to prove the effectiveness of the developed syste

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 192

This bibliography lists 247 reports, articles, and other documents introduced into the NASA scientific and technical information system in March 1979