Abstract This paper is concerned with the problem where a mobile robot of size D has to navigate to a target in an unknown planar environment. The competitiveness of an on-line navigation algorithm measures its path length relative to the length of the optimal off-line path. While competitiveness usually means constant relative performance, it is generalized here to any functional relationship between online performance and optimal off-line solution. This paper describes a new on-line navigation algorithm, called CBUG, which requires constant memory and has a quadratic competitive performance. Moreover, it is shown that in general any on-line navigation algorithm must have at least a quadratic competitive performance. The CBUG algorithm achieves the quadratic lower bound and thus has optimal competitiveness. The algorithm is improved with some practical speedups and its performance is illustrated in office-like environments.