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Published byOsborn Henry Modified over 9 years ago
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Maxim A. Batalin, Gaurav S. Sukhatme Presented by:Shawn Kristek
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A robot has networked sensor nodes that it can deploy. These static nodes then suggest the least recent direction taken when visited. i.e. An intelligent breadcrumb trail for robots
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Problem Definition Algorithm Analysis Simulations Implementation Conclusions
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Problem Definition Algorithm Analysis Simulations Implementation Conclusions
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Quick Facts Goals Coverage Exploration Based on the deployment of static, communication-enabled, sensor nodes No localization or maps Unlimited active nodes assumed
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The Nodes Heart of this work Simple computation Sensing Small Processor Simple communication Limited range radio Forms a sensor network / support infrastructure – the breadcrumb trail
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The robot Uses the nodes to solve the coverage problem Only uses local data from closest node Goal is to visit least recently visited (LRV) node Robot visiting/dropping node Forward moving robot
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Problem Definition Algorithm Analysis Simulations Implementation Conclusions
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R = receive NODE_INFO messages from nodes in vicinity if out of SHORT communication range with n then (n closest, d closest ) = node and corresponding direction in R with largest signal strength if n ≠ NULL then Send(UPDATE_DIR, n closest, d closest ) Send(UPDATE_DIR, n closest, Opposite(d closest )) else deploy sensor node n ' with suggested direction d ' (n closest, d closest ) = (n ‘, d ‘) if no obstacles detected in direction d closest (n,d ) = (n closest, d closest ) else Send(UPDATE_DIR, n closest, d closest ) Wait for response, repeat the check if moving and obstacle detected ≤ OBSTACLE_AVOIDANCE_RANGE then if obstacle is large and no nodes in vicinity deploy sensor node n‘ with suggested direction d ‘ (n,d ) = (n ‘, d ‘) if obstacles detected in direction d then Send(UPDATE_DIR, n, d ) Wait for response, repeat the check else avoid the obstacle if d = NULL then Move in direction d n, d – current node and suggested direction R – set containing data received from nodes in robot’s vicinity (node id, signal strength, suggested direction); SHORT – communication range threshold used to determine when to deploy new nodes; Opposite(d) – function returning direction opposite to d Robot
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Repeat: if received UPDATE_DIR message from robot with direction d update then W (d update ) = W (d update ) +1 Send(NODE_INFO, n, ANY_OF(arg min ∀ d Є D( i ) W (d )) ) n, d – current node and suggested direction D(i)– set of direction incident to node i, the possible directions W(d) – number of times direction d traversed from this node ANY_OF(G) – function returns member of set G according to arbitrary rule; ex. ordered, or random Node What it does: Waits for updates and sends directions, based on updates.
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LRV in Action Initially no nodes -Robot starts by deploying a node Next nodes deployed are networked to at least one other node This continues indefinitely or until no new nodes are required The robot then continually covers the environment
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Problem Definition Algorithm Analysis Simulations Implementation Conclusions
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Graphs Trees Lattice Note: The algorithm uses none of these. This is for analysis only.
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On Graphs Treat nodes as the vertices of a graph even though no explicit adjacency lists are maintained at each node Analyze the steady state n – current node the robot is at n’ – next node; the node the robot transitions to while Cover/Explored the graph = FALSE do n’ = ANY_OF(argmin ∀ j E(n) W(n, j )) W(n, n’ ) := W(n, n’ ) +1 n := n’
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On Trees Complete The least weight edge is selected Trees - graphs without cycles Exploration time Θ(2|E|) or Θ(n)
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On a Lattice Special case graph Why is this applicable? -Implementation utilizes compass with k bits and 2 k directions -Analyze case of several equal W(e)
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What they found for a Square Lattice LRV coverage O(V 1+Є )
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More Comparison LRV 1-LRTA* DFS n – current node the robot is at n’ – next node; the node the robot transitions to while Cover/Explored the graph = FALSE do n’ = ANY_OF(argmin ∀ j E(n) W( j )) W(n) := W(n’) +1 n := n’
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Convergence Speed RW LRV 1-LRTA*
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Square Lattice Assumptions DFS All resources available -Nodes -Map -Localization -Perfect navigation Limited number of simple nodes 1-LRTA* Graph exploration algorithm Not purely local
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On a Cube Lattice
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Cube/Square Lattice Ordered selection instead of random Tie breakers – optimal time more likely 1 2 3 4 Circle 1 2 3 4 Line 12 3 4 Cross
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Effects of Order Choices – Cover Time Maps Random Cross Line Circle Darker – more time
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Problem Definition Algorithms Analysis Simulations Implementation Conclusions
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Follows Problem Definition Player / Stage Pioneer 2DX robots 1.5m,180 ˚ fov planar laser range finder Wireless communication Differences: Cover time – laser Noise
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Problem Definition Algorithms Analysis Simulations Implementation Conclusions
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Nodes Recommend direction The four cardinal directions; i.e. 2 bit compass Each direction - OPEN or EXPLORED OPEN first T – binary state (OPENED, EXPLORED) C – counter for a direction E – possible additional information
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Robot Behavior-based decisions Obstacles Node locations Node recommendations
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Problem Definition Algorithm Analysis Simulations Implementation Conclusions
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Feasible applications Network repair/maintenance Questionable Comparisons Graph algorithms??? Overall good results/ideas Coverage times less than O(n ln n) Self healing – dead nodes replaced Simple
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