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In this work, we propose a collision-free source-seeking control frameworkfor unicycle robots traversing an unknown cluttered environment. In thisframework, obstacle avoidance is guided by the control barrier functions (CBF)embedded in quadratic programming and the source seeking control relies solelyon the use of on-board sensors that measure the signal strength of the source.To tackle the mixed relative degree of the CBF, we proposed three differentCBFs, namely the zeroing control barrier functions (ZCBF), exponential controlbarrier functions (ECBF), and reciprocal control barrier functions (RCBF) thatcan directly be integrated with our recent gradient-ascent source-seekingcontrol law. We provide rigorous analysis of the three different methods andshow the efficacy of the approaches in simulations using Matlab, as well as,using a realistic dynamic environment with moving obstacles in Gazebo/ROS.

Collision-free Source Seeking Control Methods for Unicycle Robots