Precise ego-motion measurement is crucial for various applications, including robotics, augmented reality, and autonomous navigation. In this poster, we propose mmPhase, an odometry framework based on single-chip millimetre-wave (mmWave) radar for robust ego-motion estimation in mobile platforms without requiring additional modalities like the visual, wheel, or inertial odometry. mmPhase leverages a phase-based velocity estimation approach to overcome the limitations of conventional doppler resolution. For real-world evaluations of mmPhase we have developed an ego-vehicle prototype. Compared to the state-of-the-art baselines, mmPhase shows superior performance in ego-velocity estimation.

翻译：精确的自运动测量对于机器人、增强现实和自主导航等多种应用至关重要。在本文中，我们提出mmPhase，一种基于单芯片毫米波雷达的里程计框架，用于在移动平台上实现鲁棒的自运动估计，无需依赖视觉、轮式或惯性里程计等额外模态。mmPhase采用基于相位的速度估计方法，以克服传统多普勒分辨率的局限性。为对mmPhase进行实际评估，我们开发了自车原型。与当前最先进的基线方法相比，mmPhase在自速度估计方面表现出优越性能。