Abstract
The infotaxis scheme is a search strategy for a diffusive source, where the sensor platform is driven to reduce the uncertainty about the source through climbing the information gradient. The infotaxis scheme has been successfully applied in many source searching tasks and has demonstrated fast and stable searching capabilities. However, the infotaxis scheme focuses on gathering information to reduce the uncertainty down to zero, rather than chasing the most probable estimated source when a reliable estimation is obtained. This leads the sensor to spend more time exploring the space and yields a longer search path. In this paper, from the context of exploration-exploitation balance, a novel search scheme based on minimizing free energy that combines the entropy and the potential energy is proposed. The term entropy is implemented as the exploration to gather more information. The term potential energy, leveraging the distance to the estimated sources, is implemented as the exploitation to reinforce the chasing behavior with the receding of the uncertainty. It results in a faster effective search strategy by which the sensor determines its actions by minimizing the free energy rather than only the entropy in traditional infotaxis. Simulations of the source search task based on the computational plume verify the efficiency of the proposed strategy, achieving a shorter mean search time.
Highlights
Autonomous robots carrying appropriate sensors can be deployed to efficiently localize the source of a biochemical or radiological contaminant leakage, such as an oil spill or a radioactive dispersal, and track the contaminant dispersion in turbulent flows [1,2]
To balance exploration-exploitation and speed up the search progress, we propose a novel search scheme that minimizes the combination of entropy and potential energy, formalized as a form of free energy [15,21,22], where the mobile sensor platform determines its search action towards the minimization of the free energy
The sensor platform at rk autonomously decides on the control variable uk using the free energy infotaxis strategy, which can be formulated as a partially-observed Markov decision process (POMDP) [16]
Summary
Autonomous robots carrying appropriate sensors can be deployed to efficiently localize the source of a biochemical or radiological contaminant leakage, such as an oil spill or a radioactive dispersal, and track the contaminant dispersion in turbulent flows [1,2]. A class of probabilistic search strategies referred to as infotaxis [14] is used for seeking the diffusive source in a turbulent medium, which determines actions to reduce the uncertainty about the source through minimizing the entropy of the source probability distribution. The expected reduction of the entropy is implemented as the exploration term (that is, gathering more information and obtaining a more reliable estimate of the source distribution) and the maximum likelihood as the exploitation term (that is, going to the estimated most probable source location) [20]. There exists an exploitation term playing the role of the maximum likelihood It employs the local probability around the sensor for the maximum likelihood, which prevents the chasing behavior from being led off the track with the receding of uncertainty after acquiring more detections.
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