Improving Radio Energy Harvesting in Robots using Mobility Diversity

In this paper, we propose a new technique that exploits a robot's (intelligently) controlled mobility to maximize stored radio energy. In particular, we examine a scenario where the mobile robot takes a break from its normal activity for a duration of T s. This “dead time” consists of three phases-searching, positioning, and resting-which ensure that the robot can optimize its energy harvesting from a base station transmitting a narrowband RF signal over a flat-fading wireless channel. We utilize the mobility diversity principle, which arises due to the spatial wireless channel diversity experienced by motion of the robot. By optimal exploitation of the small scale fading, we maximize the net amount of energy (i.e., the energy harvested by the robot minus the mechanical energy used for motion) that the robot stores over the “dead time”. To the best of the authors' knowledge, this paper is the first use of the mobility diversity principle to optimize energy harvesting from an RF signal. We demonstrate that mobility, if intelligently controlled, is actually not a foe but is indeed a friend that can provide significant benefits under wireless fading channels. Through simulations, we verify the analytical results and illustrate the improvement in the energy stored compared with not using intelligent mobility. Finally, we show that the efficiency of our approach is clearly coupled with various design parameters, including the center frequency of the narrowband RF signal and the duration of the “dead time”.