  We develop a novel adaptation-based technique for safe control design in the
presence of multiple control barrier function (CBF) constraints. Specifically,
we introduce an approach for synthesizing any number of candidate CBFs into one
consolidated CBF candidate, and propose a parameter adaptation law for the
weights of its constituents such that the controllable dynamics of the
consolidated CBF are non-vanishing. We then prove that the use of our
adaptation law serves to certify the consolidated CBF candidate as valid for a
class of nonlinear, control-affine, multi-agent systems, which permits its use
in a quadratic program based control law. We highlight the success of our
approach in simulation on a multi-robot goal-reaching problem in a crowded
warehouse environment, and further demonstrate its efficacy experimentally in
the laboratory via AION ground rovers operating amongst other vehicles behaving
both aggressively and conservatively.
