Grid, place, and border cells in the mammalian hippocampus and entorhinal cortex perform highly sophisticated navigational tasks with an extremely low power budget. While previous algorithms for simultaneous localization and mapping (SLAM) in robotics have used these cells for inspiration, they have sacrificed the robust, low-power gains achieved with bioplausible models for ease of implementation. This paper presents steps towards robotic navigation with biologically realistic hippocampal models by implementing velocity-controlled oscillators, a basis for any spatially-tuned neuron, on mixed-mode neuromorphic spiking hardware.