A fundamental challenge in robot perception is the coupling of the sensor pose and robot pose. This has led to research in active vision where robot pose is changed to reorient the sensor to areas of interest for perception. Further, egomotion such as jitter, and external effects such as wind and others affect perception requiring additional effort in software such as image stabilization. This effect is particularly pronounced in micro-air vehicles and micro-robots who typically are lighter and subject to larger jitter but do not have the computational capability to perform stabilization in real-time. We present a novel microelectromechanical (MEMS) mirror LiDAR system to change the field of view of the LiDAR independent of the robot motion. Our design has the potential for use on small, low-power systems where the expensive components of the LiDAR can be placed external to the small robot. We show the utility of our approach in simulation and on prototype hardware mounted on a UAV. We believe that this LiDAR and its compact movable scanning design provide mechanisms to decouple robot and sensor geometry allowing us to simplify robot perception. We also demonstrate examples of motion compensation using IMU and external odometry feedback in hardware.

翻译：机器人感知中的一项基本挑战在于传感器位姿与机器人位姿的耦合问题。这促使研究者探索主动视觉领域，通过改变机器人位姿重新定向传感器至感兴趣区域以完成感知任务。此外，自运动（如抖动）以及外部环境因素（如风力等）会进一步影响感知性能，需要在软件层面额外增加图像稳定等处理措施。这种影响在微型飞行器与微型机器人中尤为显著——这类设备通常质量较轻且承受更大抖动，却缺乏实时完成运动补偿的计算能力。我们提出一种基于微机电系统（MEMS）反射镜的新型激光雷达系统，可独立于机器人运动改变其视场角。该设计适用于小型低功耗系统，其中激光雷达的高成本组件可置于小型机器人外部。我们通过仿真实验和安装在无人机上的原型硬件验证了本方法的有效性。我们认为，该激光雷达及其紧凑型可移动扫描设计为解耦机器人与传感器几何关系提供了新机制，从而简化机器人感知任务。我们还在硬件平台上演示了基于惯性测量单元（IMU）和外部里程计反馈的运动补偿示例。