Abstract. We present an interpolation-based planning and replanning algorithm for generating smooth paths through non-uniform cost grids. Most grid-based path planners use discrete state transitions that artificially constrain an agent’s motion to a small set of possible headings (e.g. 0, π 4 , π 2 , etc). As a result, even the ‘optimal’ grid planners produce unnatural, suboptimal paths. Our approach uses linear interpolation during planning to calculate accurate path cost estimates for arbitrary positions within each grid cell and to produce paths with a continuous range of headings. Consequently, it is particularly well suited to planning smooth, least-cost trajectories for mobile robots. In this paper, we present a number of applications and results, a comparison to related algorithms, and several implementations on real robotic systems.