铰接履带式机器人的无地图、稳定化及防卡滞 flipper 控制
Mapless, Stabilizing, and Anti-Stuck Flipper Control for Articulated Tracked Robots
AI总结：
针对铰接履带式机器人，提出无地图的SAS控制器，融合稳定与防卡滞功能，在仿真和真实场景中，其 traversal 质量媲美先进基于地图控制器，且能通过LiDAR无法探测的隐藏障碍物。
摘要：
几乎所有自主或半自主的 flipper 控制器都假设可获取机器人下方及前方地形的高程地图。底盘下方的地形会被传感器遮挡，因此该地图需通过里程计积分进行记忆，而里程计积分的漂移会导致地图损坏。我们提出 Stabilizing Anti-Stuck（SAS，稳定化防卡滞）控制器，这是一种无地图控制器，它将用于机身横滚和俯仰的稳定项与机器人卡滞时使其脱困的防卡滞项相结合。SAS 的输入为 IMU（惯性测量单元）、flipper 关节角度以及仅指示机器人是否移动的运动提示。该提示在短时间窗口内计算且永不累积，因此 SAS 不会继承损坏地图的里程计积分漂移。我们将 SAS 部署在带有四个 flipper 的履带式机器人上，并在仿真和真实障碍物上的大规模对比实验中，将其与手动遥操作及现有 flipper 控制器进行评估。在仿真和真实机器人上，SAS 实现了与最先进的基于地图控制器相当的 traversal quality（ traversal 质量）。在 LiDAR（激光雷达）无法探测到的高草中隐藏的原木上，表现最佳的基于地图的控制器发生卡滞，而 SAS 则顺利通过了该隐藏障碍物。
英文摘要：
Nearly every autonomous or semi-autonomous flipper controller assumes access to an elevation map of the terrain under and in front of the robot. The terrain beneath the chassis is occluded in the sensors, so the map is remembered through odometry integration, whose drift corrupts it. We present Stabilizing Anti-Stuck (SAS), a mapless controller that combines a stabilization term for body roll and pitch with an anti-stuck term that frees the robot when it gets stuck. As input, SAS uses the IMU, the flipper joint angles, and a motion cue that only tells whether the robot is moving. The cue is computed over a short window and never accumulated, so SAS does not inherit the odometry-integration drift that corrupts the map. We deploy SAS on a tracked robot with four flippers and evaluate it against manual teleoperation and prior flipper controllers in a large comparison, both in simulation and on a real obstacle. In simulation and on the real robot, SAS achieves traversal quality comparable to state-of-the-art map-based controllers. On a log hidden in tall grass, invisible to the LiDAR, the best map-based controller gets stuck while SAS traverses the hidden obstacle without a problem.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
