TY - JOUR

T1 - SLAM for pedestrians and ultrasonic landmarks in emergency response scenarios

AU - Fischer, Carl

AU - Muthukrishnan, Kavitha

AU - Hazas, Michael

PY - 2011

Y1 - 2011

N2 - Providing ad hoc solutions for positioning and tracking of emergency response teams is an important and safety-critical challenge. Although solutions based on inertial sensing systems are promising, they are subject to drift. We address the problem of positional drift by having the responders themselves deploy sensor nodes capable of sensing range and angle-of-arrival, as they progress into an unknown environment. Our research focuses on a sensor network approach that does not rely on preexisting infrastructure. This chapter targets two important aspects of such a solution: how to locate the deployed static sensor nodes, and how to track the responders by using a combination of ultrasound and inertial measurements. The main contributions of this chapter are: (i) a characterization of the errors encountered in inertial-based pedestrian dead-reckoning as well as ultrasound range and bearing measurements in a mobile setting, (ii) the formulation of an extended Kalman filter for simultaneously locating sensor nodes and tracking a pedestrian using a combination of ultrasound range/bearing measurements and inertial measurements, and (iii) the validation of the presented algorithms using data collected from real deployments.

AB - Providing ad hoc solutions for positioning and tracking of emergency response teams is an important and safety-critical challenge. Although solutions based on inertial sensing systems are promising, they are subject to drift. We address the problem of positional drift by having the responders themselves deploy sensor nodes capable of sensing range and angle-of-arrival, as they progress into an unknown environment. Our research focuses on a sensor network approach that does not rely on preexisting infrastructure. This chapter targets two important aspects of such a solution: how to locate the deployed static sensor nodes, and how to track the responders by using a combination of ultrasound and inertial measurements. The main contributions of this chapter are: (i) a characterization of the errors encountered in inertial-based pedestrian dead-reckoning as well as ultrasound range and bearing measurements in a mobile setting, (ii) the formulation of an extended Kalman filter for simultaneously locating sensor nodes and tracking a pedestrian using a combination of ultrasound range/bearing measurements and inertial measurements, and (iii) the validation of the presented algorithms using data collected from real deployments.

U2 - 10.1016/B978-0-12-385514-5.00003-3

DO - 10.1016/B978-0-12-385514-5.00003-3

M3 - Journal article

VL - 81

SP - 103

EP - 160

JO - Advances in Computers

JF - Advances in Computers

ER -