Urban Propagation Modeling for Wireless Systems

IEEE Trans. Wireless Commun.

2013

Abstract-We consider the scenario where a robot is tasked with sending a fixed number of given bits of information to a remote station, in a limited operation time, as it travels along a pre-defined trajectory, and while minimizing its motion and communication energy costs. We propose a co-optimization framework that allows the robot to plan its motion speed, transmission rate and stop time, based on its probabilistic prediction of the channel quality along the trajectory. We show that in order to save energy, the robot should move faster (slower) and send less (more) bits at the locations that have worse (better) predicted channel qualities. We furthermore prove that if the robot must stop, it should then stop only once and at the location with the best predicted channel quality. We also prove some properties for two special scenarios: the heavy-task load and the light-task load cases. We also propose an additional stop-time online adaptation strategy to further fine tune the stop location as the robot moves along its trajectory and measures the true value of the channel. Finally, our simulation results show that our proposed framework results in a considerable performance improvement.

“…In this section, we test our framework by using real channel measurements from downtown San Francisco (data courtesy of W. M. Smith) [23].…”

Section: Simulation Resultsmentioning

confidence: 99%

Section: Simulation Resultsmentioning

confidence: 99%

Co-Optimization of Communication and Motion Planning of a Robotic Operation under Resource Constraints and in Fading Environments

Yuan

IEEE Trans. Wireless Commun.

2013

“…5 (left and right). The channel in the workspace is generated with the following real channel parameters from downtown San Francisco [27]: path loss exponent is 4.57, standard deviation of shadowing is 4, decorrelation distance of shadowing is 3.52 m, and the multipath fading is Rician fading with Rician parameter of 5.9. The channel is extended to populate the space of interest using our probabilistic channel simulator [28].…”

Section: Simulation Resultsmentioning

confidence: 99%

Efficient communication-aware dynamic coverage using space-filling curves

Yuan

2014 American Control Conference

2014

Abstract-In this paper, we consider a dynamic coverage problem where a team of mobile robots needs to cover a set of time-varying Points of Interest (POIs), while maintaining their connectivity to a remote station in a realistic communication environment. Our goal is to design the motion and communication strategies of the robots such that they periodically visit the POIs, communicate the gathered information to a remote station, minimize their total energy costs, including motion, sensing and communication energy, and satisfy other system constraints. In our previous work [1], we have shown how to pose this problem as a Mixed Integer Linear Program (MILP), which is computationally expensive. In this paper, we focus on designing a considerably more computationally-efficient heuristic approach to tackle this problem. More specifically, we propose to utilize the space-filling curves to efficiently assign the POIs and plan the trajectories of the robots. Under certain conditions, we mathematically show that our heuristic approach is at most a constant factor away from the global optimum. Our simulation results then confirm that our approach is considerably faster than solving the MILP, especially when the dimension of the problem is high. They further show that the energy consumption of our approach is only around 26% more than the optimum.

“…This can help the readers understand the conditions under which our measurements are collected so that they can reproduce the results. Traditionally, there has been considerable interest in measurement and characterization of the received communication signal strength in the context of cellular systems [18][19][20][21][22]. Automating the measurement process, however, has been difficult in the past due to the lack of an automated mobile system.…”

Section: An Experimental Robotic Platform For Channel Measurement Colmentioning

confidence: 99%

A Comprehensive Overview and Characterization of Wireless Channels for Networked Robotic and Control Systems

Gonzalez-Ruiz

Ghaffarkhah

2011

Journal of Robotics

The goal of this overview paper is to serve as a reference for researchers that are interested in the realistic modeling of wireless channels for the purpose of analysis and optimization of networked robotic systems. By utilizing the knowledge available in the wireless communication literature, we first summarize a probabilistic framework for the characterization of the underlying multiscale dynamics of a wireless link. We furthermore confirm this framework with our robotic testbed, by making an extensive number of channel measurements. To show the usefulness of this framework for networked robotic applications, we then discuss a few recent examples where this probabilistic channel characterization has been utilized for the theoretical analysis and communication-aware design of networked robotic systems. Finally, we show how to develop a realistic yet simple channel simulator, which can be used to verify cooperative robotic operations in the presence of realistic communication links.