Abstract-A simple approach for mobile robots to exploit multipath fading in order to improve received radio signal strength (RSS), is presented. The strategy is to sample the RSS at discrete points, without deviating too far from the desired position. We first solve the problem of how many samples are needed for given communications performance and how they should be spaced. Second, we propose a circular and a grid trajectory for sampling and give lower bounds on how many samples they will yield. Third, we estimate the parameters of our strategy from measurements. Finally we demonstrate the validity of our analysis through experiments.

A new distributed coordination algorithm for multi-vehicle systems is presented in this paper. The algorithm combines a particular choice of navigation function with Voronoi partitions. This results not only in obstacle avoidance and motion to the goal, but also in a desirable geographical distribution of the vehicles. Our algorithm is decentralized in that each vehicle needs only to know the position of neighboring vehicles, but no other inter-vehicle communication or centralized control are required. The algorithm gives a natural priority to safety, goal convergence, and formation keeping, in that (1) collision avoidance is guaranteed under all circumstances, (2) the vehicles will move toward the goal as long as a given optimization problem is feasible, and (3) if prior criteria admit, the vehicles tend to a desirable lattice formation. These theoretical properties are discussed in the paper and the performance of the algorithm is illustrated in simulations with realistic models of twenty all-terrain vehicles. Planned experimental evaluation using customized miniature cars is also briefly described.

Communication-aware motion control allows mobile networked robots to increase the average communication throughput. We exploit that in a multipath fading channel, robots can measure the SNR and adapt their motion to spend slightly more time at positions where the channel is good. Two new such cross-layer strategies are analyzed and evaluated: periodic stopping, where the stop duration is a function of the SNR, and controlled stopping, where the robot stops when the communication buffer is filling up. It is shown that the expected average channel capacity can be twice as high as when no cross-layer information is utilized. Experimental evaluation of the strategies confirms the theoretical results.

Mobile wireless sensors in indoor environments will experience multipath fading, causing rapid variations in the capacity of the radio link. We present a strategy that increases the throughput by modifying the trajectory of the sensor so it spends more time at positions where the capacity is high. While doing so, it still maintains some desired average velocity. Our approach includes closed-loop estimation of the parameters of the fading, which may change when moving between rooms. We prove stability of the feedback system and illustrate its behavior through simulations. Finally, we demonstrate robustness to errors in the channel model.

In indoor or urban applications, a moving robot with wireless communications will experience multipath fading. This causes rapid signal strength variations due to interfering reflections of the radio signal. By making short stops at positions with high signal-to-noise ratio (SNR), the robot can trade trajectory tracking accuracy for increased link quality. This represents a type of opportunistic communication-aware motion planning. We propose two novel strategies for improving the link capacity or throughput when either the robot has full knowledge of how the SNR varies along the trajectory, or when only the SNR distribution is known or can be estimated. In the latter case, this leads to an optimal stopping problem over a finite horizon. Both cases are analyzed for independent as well as correlated SNR samples, and a bounded maximum trajectory tracking error. We derive the resulting SNR distributions for the proposed strategies and use them to show how the expected capacity and throughput vary with the allowed tracking error. The results are confirmed by simulations and experiments. Experiments in six different locations validate the communication model and show that the proposed motion planning is robust to non-static fading and can yield throughput improvements of more than 100%.