Navigation protocols in sensor networks

Abstract

We develop distributed algorithms for adaptive sensor networks that respond to directing a target through a region of space. We model this problem as an online distributed motion planning problem. Each sensor node senses values in its perception space and has the ability to trigger exceptions events we call "danger" and model as "obstacles". The danger/obstacle landscape changes over time. We present algorithms for computing distributed maps in perception space and for using these maps to compute adaptive paths for a mobile node that can interact with the sensor network. We give the analysis to the protocol and report on hardware experiments using a physical sensor network consisting of Mote sensors. We also show how to reduce searching space and communication cost using Voronoi diagram.to triggers from the environment. Distributed adaptive sensor networks are reactive computing systems, well suited for tasks in extreme environments, especially when the environmental model and the task specifications are uncertain and the system has to adapt to them. A collection of active sensor networks can follow the movement of a source to be tracked, for example, a moving vehicle. It can guide the movement of an object on the ground, for example, a surveillance robot. Or it can focus attention over a specific area, for example, a fire in order to localize its source and track its spread.A sensor network consists of a collection of sensors distributed over some area that form an ad hoc network. Each sensor is equipped with some limited memory and processing capabilities, multiple sensing modalities, and communication capabilities. Previous work in sensor networks has concentrated on routing protocols for sensor networks. Often the network topology is unknown and the network has to discover the best route for a packet. Optimization criteria include shortest path to destination, minimum power utilization, maximum minimum residual power in the network, and so forth.In this article, we focus on a reactive task in sensor networks: guiding the movement of a user equipped with a node that can talk to the field of sensors across the field. We also discuss how sensor networks can serve as adaptive distributed repositories of information. We model the user guidance problem as a robot motion planning problem and use the inherent feature of the sensor network to compute the robot navigation path in a distributed way. Our article contributes (1) a mobile application for sensor network; (2) an implementation and evaluation on a physical sensor network; (3) a distance computation method that does not use node positions; (4) performance analysis and hardware experimentation; (5) variation of the navigation protocols that reduces the searching space using Voronoi diagrams.

Escape planning in realistic fire scenarios with Ant Colony Optimisation

“…Thus, at a given time n the environment updates the function in line with (1) and makes all hazards exactly opposite. This produces a particularly difficult situation since an (near) optimal route changes to as far away from optimal as possible, and algorithms which have learnt an optimal route will need to completely relearn its learnt behaviour.…”

“…Similarly, the emergency personnel often lack an overview of where people are located and which rooms are affected by hazards. This makes evacuation planning particularly difficult [1,2].…”

Cooperative navigation in robotic swarms

“…One setup that has been studied extensively over the past few years is to fit the environment with a network of wireless communication nodes, which guide a single robot to a target [55], [3]. The communication nodes may be wireless sensor nodes, which sense the local environment and take this sensed information into account when planning a path [56], or sensor-less nodes, which use only communication for path planning [17]. Many of these approaches use communication links to define obstacle-free paths, e.g., using infrared communication [3], so that they can use network routing algorithms to define navigation paths.…”

Using a wireless visual sensor network to harmonically navigate multiple low-cost wheelchairs in an indoor environment

“…In such applications, neither network nodes nor mobile robots need to know their positions or build any kind of map [34], and mobile robots are guided autonomously between different locations by the navigation network. These applications also aimed at building an intelligent environment to support the robot navigation, and they preferably find shortest possible paths while avoiding dangers in the environment [24], and collisions with static obstacles [34], and other mobile objects. Motivated by the characteristic of this kind of network, we have described a solution [17,40], in which wireless visual sensor nodes (WVSnode) are distributed in an intelligent environment to support navigation of a robotic wheelchair.…”