70,331 research outputs found
Selecting source image sensor nodes based on 2-hop information to improve image transmissions to mobile robot sinks in search \& rescue operations
We consider Robot-assisted Search Rescue operations enhanced with some
fixed image sensor nodes capable of capturing and sending visual information to
a robot sink. In order to increase the performance of image transfer from image
sensor nodes to the robot sinks we propose a 2-hop neighborhood
information-based cover set selection to determine the most relevant image
sensor nodes to activate. Then, in order to be consistent with our proposed
approach, a multi-path extension of Greedy Perimeter Stateless Routing (called
T-GPSR) wherein routing decisions are also based on 2-hop neighborhood
information is proposed. Simulation results show that our proposal reduces
packet losses, enabling fast packet delivery and higher visual quality of
received images at the robot sink
A Novel Communications Protocol Using Geographic Routing for Swarming UAVs Performing a Search Mission
This research develops the UAV Search Mission Protocol (USMP) for swarming UAVs and determines the protocol\u27s effect on search mission performance. It is hypothesized that geographically routing USMP messages improves search performance by providing geography-dependent data to locations where it impacts search decisions. It is also proposed that the swarm can use data collected by the geographic routing protocol to accurately determine UAV locations and avoid sending explicit location updates. The hypothesis is tested by developing several USMP designs that are combined with the Greedy Perimeter Stateless Routing (GPSR) protocol and a search mission swarm logic into a single network simulation. The test designs use various transmission power levels, sensor types and swarm sizes. The simulation collects performance metrics for each scenario, including measures of distance traveled, UAV direction changes, number of searches and search concentration. USMP significantly improves mission performance over scenarios without inter-UAV communication. However, protocol designs that simply broadcast messages improve search performance by 83% in total searches and 20% in distance traveled compared to geographic routing candidates. Additionally, sending explicit location updates generates 3%-6% better performance per metric versus harvesting GPSR\u27s location information
Symmetry-Based Search Space Reduction For Grid Maps
In this paper we explore a symmetry-based search space reduction technique
which can speed up optimal pathfinding on undirected uniform-cost grid maps by
up to 38 times. Our technique decomposes grid maps into a set of empty
rectangles, removing from each rectangle all interior nodes and possibly some
from along the perimeter. We then add a series of macro-edges between selected
pairs of remaining perimeter nodes to facilitate provably optimal traversal
through each rectangle. We also develop a novel online pruning technique to
further speed up search. Our algorithm is fast, memory efficient and retains
the same optimality and completeness guarantees as searching on an unmodified
grid map
Bidirectional Heuristic Search Reconsidered
The assessment of bidirectional heuristic search has been incorrect since it
was first published more than a quarter of a century ago. For quite a long
time, this search strategy did not achieve the expected results, and there was
a major misunderstanding about the reasons behind it. Although there is still
wide-spread belief that bidirectional heuristic search is afflicted by the
problem of search frontiers passing each other, we demonstrate that this
conjecture is wrong. Based on this finding, we present both a new generic
approach to bidirectional heuristic search and a new approach to dynamically
improving heuristic values that is feasible in bidirectional search only. These
approaches are put into perspective with both the traditional and more recently
proposed approaches in order to facilitate a better overall understanding.
Empirical results of experiments with our new approaches show that
bidirectional heuristic search can be performed very efficiently and also with
limited memory. These results suggest that bidirectional heuristic search
appears to be better for solving certain difficult problems than corresponding
unidirectional search. This provides some evidence for the usefulness of a
search strategy that was long neglected. In summary, we show that bidirectional
heuristic search is viable and consequently propose that it be reconsidered.Comment: See http://www.jair.org/ for any accompanying file
Movement around real and virtual cluttered environments
Two experiments investigated participants’ ability to search for targets in a cluttered small-scale space. The first experiment was conducted in the real world with two field of view conditions (full vs. restricted), and participants found the task trivial to perform in both. The second experiment used the same search task but was conducted in a desktop virtual environment (VE), and investigated two movement interfaces and two visual scene conditions. Participants restricted to forward only movement performed the search task quicker and more efficiently (visiting fewer targets) than those who used an interface that allowed more flexible movement (forward, backward, left, right, and diagonal). Also, participants using a high fidelity visual scene performed the task significantly quicker and more efficiently than those who used a low fidelity scene. The performance differences between all the conditions decreased with practice, but the performance of the best VE group approached that of the real-world participants. These results indicate the importance of using high fidelity scenes in VEs, and suggest that the use of a simple control system is sufficient for maintaining ones spatial orientation during searching
Movement around real and virtual cluttered environments
Two experiments investigated participants’ ability to search for targets in a cluttered small-scale space. The first experiment was conducted in the real world with two field of view conditions (full vs. restricted), and participants found the task trivial to perform in both. The second experiment used the same search task but was conducted in a desktop virtual environment (VE), and investigated two movement interfaces and two visual scene conditions. Participants restricted to forward only movement performed the search task quicker and more efficiently (visiting fewer targets) than those who used an interface that allowed more flexible movement (forward, backward, left, right, and diagonal). Also, participants using a high fidelity visual scene performed the task significantly quicker and more efficiently than those who used a low fidelity scene. The performance differences between all the conditions decreased with practice, but the performance of the best VE group approached that of the real-world participants. These results indicate the importance of using high fidelity scenes in VEs, and suggest that the use of a simple control system is sufficient for maintaining ones spatial orientation during searching
Changes in navigational behaviour produced by a wide field of view and a high fidelity visual scene
The difficulties people frequently have navigating in virtual environments (VEs) are well known. Usually these
difficulties are quantified in terms of performance (e.g., time taken or number of errors made in following a path),
with these data used to compare navigation in VEs to equivalent real-world settings. However, an important cause
of any performance differences is changes in people’s navigational behaviour. This paper reports a study that
investigated the effect of visual scene fidelity and field of view (FOV) on participants’ behaviour in a navigational
search task, to help identify the thresholds of fidelity that are required for efficient VE navigation. With a wide FOV
(144 degrees), participants spent significantly larger proportion of their time travelling through the VE, whereas
participants who used a normal FOV (48 degrees) spent significantly longer standing in one place planning where
to travel. Also, participants who used a wide FOV and a high fidelity scene came significantly closer to conducting
the search "perfectly" (visiting each place once). In an earlier real-world study, participants completed 93% of
their searches perfectly and planned where to travel while they moved. Thus, navigating a high fidelity VE with
a wide FOV increased the similarity between VE and real-world navigational behaviour, which has important
implications for both VE design and understanding human navigation.
Detailed analysis of the errors that participants made during their non-perfect searches highlighted a dramatic
difference between the two FOVs. With a narrow FOV participants often travelled right past a target without it
appearing on the display, whereas with the wide FOV targets that were displayed towards the sides of participants
overall FOV were often not searched, indicating a problem with the demands made by such a wide FOV display
on human visual attention
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