Asynchronous Multi-Centralized Cooperative Localization

Abstract

Abstract-This paper presents a generalized framework for inter-robot information-transfer schemes in Multi-Centralized Cooperative Localization (MC-CL) under asynchronous communication, i.e., when the communication graph associated with the mobile robot network is time-varying and intermittently disconnected. Specifically, two information-transfer schemes, which differ based on their communication bandwidth requirements per link, are discussed. Even under asynchronous communication constraints, these schemes enable robots to compute pose estimates identical to those generated using the centralized CL framework, albeit delayed. For each of these schemes, necessary and sufficient conditions for the communicationgraph connectivity, that enable each robot to generate the centralized estimates, are developed. Moreover, detailed description of these schemes, along with their communication-complexity analysis and analytical results for the expected time delay in obtaining these estimates, are presented. Lastly, simulation results are used to validate the performance (the trade-off between communication link bandwidth and accuracy/delay) of these information-transfer schemes.

Decentralized cooperative trajectory estimation for autonomous underwater vehicles

“…Several methods are capable of handling asynchronous communications such as [23], [12], [22]. For example, [23], provides a framework for deciding under what conditions raw data can be replaced by filtered estimates.…”

“…For example, [23], provides a framework for deciding under what conditions raw data can be replaced by filtered estimates. Similarly in [12] a delayed-state filter is proposed. These works have two notably shortcomings for implementation underwater: first, filtering approaches will always require the transmission of the joint state covariance matrix which scales O(N 2 ) where N is the size of the robot team, and secondly, data backlog over extended periods of disconnectivity between nodes is problematic.…”

“…We proposed a method that draws inspiration from previous "multi-centralized" approaches where the full centralized state of the team is estimated onboard each robot [12], [13], [14]. However, in our case, the joint states estimated onboard each vehicle vary across the team.…”

Advances in integrating autonomy with acoustic communications for intelligent networks of marine robots

“…Trawny, et al [60] uses a highly quantized (as few as one bit per time step) Kalman filter dubbed the Iteratively-Quantized Extended Kalman filter (IQEKF), which they show in simulation to provide acceptable performance relative to a real valued Kalman filter. Nerurkar and Roumeliotis [61] then extend the idea to incorporate asynchronous communications (where one node cannot necessarily talk bi-directionally to another). Bahr [62], and later Fallon, et al [63] address the problem of CL on AUVs.…”

A hybrid estimation framework for Cooperative Localization under communication constraints

“…Various approaches that address this issue of resource-constrained CL have been proposed in the literature. For instance, in some cases robots select and transmit a subset of their real-valued 1 (analog) measurements depending on the communication bandwidth availability [7], [8]. However, in this paper we focus on CL under severe communication constraints where each robot can transmit only a single bit per real-valued measurement.…”