Cooperative localization by dual foot-mounted inertial sensors and inter-agent ranging
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Cooperative localization by dual foot-mounted inertial sensors and inter-agent ranging John-Olof Nilsson* , Dave Zachariah, Isaac Skog and Peter Händel
Abstract The implementation challenges of cooperative localization by dual foot-mounted inertial sensors and inter-agent ranging are discussed, and work on the subject is reviewed. System architecture and sensor fusion are identified as key challenges. A partially decentralized system architecture based on step-wise inertial navigation and step-wise dead reckoning is presented. This architecture is argued to reduce the computational cost and required communication bandwidth by around two orders of magnitude while only giving negligible information loss in comparison with a naive centralized implementation. This makes a joint global state estimation feasible for up to a platoon-sized group of agents. Furthermore, robust and low-cost sensor fusion for the considered setup, based on state space transformation and marginalization, is presented. The transformation and marginalization are used to give the necessary flexibility for presented sampling-based updates for the inter-agent ranging and ranging free fusion of the two feet of an individual agent. Finally, the characteristics of the suggested implementation are demonstrated with simulations and a real-time system implementation. Keywords: Cooperative localization; Pedestrian localization; Pedestrian dead reckoning; Inertial navigation; Infrastructure-free localization
1 Introduction High accuracy, robust, and infrastructure-free pedestrian localization is a highly desired ability for, among others, military, security personnel, and first responders. Localization and communication are key capabilities to achieve situational awareness and to support, manage, and automatize individual’s or agent group actions and interactions. See [1-8] for reviews on the subject. The fundamental information sources for the localization are proprioception, exteroception, and motion models. Without infrastructure, the exteroception must be dependent on prior or acquired knowledge about the environment [9]. Unfortunately, in general, little or no prior knowledge of the environment is available, and exploiting acquired knowledge without revisiting locations is difficult. Therefore, preferably the localization should primarily rely on proprioception and motion models. Proprioception can take place on the agent level, providing the possibility to perform dead reckoning, or on inter-agent level, *Correspondence: [email protected] Signal Processing Department, ACCESS Linnaeus Centre, KTH Royal Institute of Technology, Osquldas väg 10, SE-100 44 Stockholm, Sweden
providing the means to perform cooperative localization. Pedestrian dead reckoning can be implemented in a number of different ways [10]. However, foot-mounted inertial navigation, with motion models providing zerovelocity updates, constitute a unique, robust, and highaccuracy pedestrian dead reckoning capability [11-14]. With open-source implementations [15-1
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