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This paper proposes a method to navigate a mobile robot by estimating its state over a number of distributed sensor networks (DSNs) such that it can successively accomplish a sequence of tasks, i.e., its state enters each targeted set and stays inside no less than the desired time, under a resource-aware, time-efficient, and computation- and communication-constrained setting.We propose a new robot state estimation and navigation architecture, which integrates an event-triggered task-switching feedback controller for the robot and a two-time-scale distributed state estimator for each sensor. The architecture has three major advantages over existing approaches: First, in each task only one DSN is active for sensing and estimating the robot state, and for different tasks the robot can switch the active DSN by taking resource saving and system performance into account; Second, the robot only needs to communicate with one active sensor at each time to obtain its state information from the active DSN; Third, no online optimization is required. With the controller, the robot is able to accomplish a task by following a reference trajectory and switch to the next task when an event-triggered condition is fulfilled. With the estimator, each active sensor is able to estimate the robot state. Under proper conditions, we prove that the state estimation error and the trajectory tracking deviation are upper bounded by two time-varying sequences respectively, which play an essential role in the event-triggered condition. Furthermore, we find a sufficient condition for accomplishing a task and provide an upper bound of running time for the task. Numerical simulations of an indoor robots localization and navigation are provided to validate the proposed architecture.
This paper investigates the online motion coordination problem for a group of mobile robots moving in a shared workspace. Based on the realistic assumptions that each robot is subject to both velocity and input constraints and can have only local vie
Currently, mobile robots are developing rapidly and are finding numerous applications in industry. However, there remain a number of problems related to their practical use, such as the need for expensive hardware and their high power consumption lev
This paper investigates the online motion coordination problem for a group of mobile robots moving in a shared workspace, each of which is assigned a linear temporal logic specification. Based on the realistic assumptions that each robot is subject t
Goal: This paper presents an algorithm for accurately estimating pelvis, thigh, and shank kinematics during walking using only three wearable inertial sensors. Methods: The algorithm makes novel use of a constrained Kalman filter (CKF). The algorithm
In this paper, we develop a textcolor{black}{emph{distributed}} algorithm to localize a network of robots moving arbitrarily in a bounded region. In the case of such mobile networks, the main challenge is that the robots may not be able to find nearb