ROS 导航 move_base costmap planner 的调试说明
http://wiki.ros.org/navigation/Tutorials/Navigation%20Tuning%20Guide
1.查看传感器数据有无输出，以及频率
2.里程计测试：
（1）打开Rviz 设置frame为“odom”，display 激光， 设置topic的延时时间(decay time)为20s左右，然后原地旋转。Then, I look at how closely the scans match each other on subsequent rotations. Ideally, the scans will fall right on top of each other, but some rotational drift is expected, so I just make sure that the scans aren't off by more than a degree or two
（2）对着墙面测试里程计的平移：The next test is a sanity check on odometry for translation. I'll set up rviz the same way with the robot a few meters away from a wall. Then, I'll drive the robot straight at the wall and look at the thickness of the wall as reported by the aggregated laser scans in rviz. Ideally, the wall should look like a single scan but I just make sure that it doesn't have a thickness of more than a few centimeters. If you drive a meter towards a wall and get scans spread out over half a meter though, something is likely wrong with the odometry
3.定位：
若里程计不是很准，可以参考amcl的里程计模型参数设置进行改进：I'll play around a bit with the odometry model parameters for AMCL
4.costmap：
（1）确保每个观测源的期待更新频率（expected_update_rate）是基于传感器的发布频率，通常要给予一定量的容忍度
（2）transform_tolerance：使用tf_monitor 检查transform from the "base_link" frame to the "map" frame的时延，然后设置保守的参数
（3）map_update_rate
（4）publish_frequency 调低
（5）在里程计frame下测试导航独立与定位：Sometimes, its useful to be able to run navigation solely in the odometric frame. To do this, I find the easiest thing to do is to copy my local_costmap_params.yaml file over my global_costmap_params.yaml file and change the the width and height of the map to be something more like 10 meters. This is a really easy way to get things up and running if you want to tune navigation independent of localization performance
（6）其他 看说明
5. local planner：
（1）一定要看机器人的加速度限制
（2）对于DWA：update the vx_samples parameter to something between 8 and 15 depending on the processing power available. This will allow for non-circular curves to be generated in the rollout
（3） 定位不准和避免震荡：localization for the robot I'm working with isn't great, I'll make sure to set the goal tolerance parameters a bit higher than I would otherwise. I'll also up the rotational tolerance if the robot has a high minimum rotational velocity to avoid oscillations at the goal point.
（4）CPU不够 sim_granularity适当提高（采样间隔增加，采样数减少）
（5）Turning the path_distance_bias parameter up 更贴近路径 但设置过高会导致机器人拒绝移动，因为移动的cost远比待在路径上的cost高
（6）如何整定cost function： If I want to reason about the cost function in an intelligent way, I'll make sure to set the meter_scoring parameter to true. This makes it so distances in the cost function are in meters instead of cells and also means that I can tune the cost function for one map resolution and expect reasonable behavior when I move to others. Furthermore, you can now visualize the cost function produced by the local planner in rviz by setting the publish_cost_grid parameter to true. (This somehow never made it into the docs, I'll get to that sometime soon). Given the cost function in meters, I can compute the tradeoff in cost of moving 1 meter towards the goal balanced against how far away I am from the planned path. This tends to give me a decent idea of how to tune things
（7）轨迹室友他们的终点endpoint打分的，这意味着设置不同的sim_time 将对机器人行为产生很大的影响，一般设置在1-2秒，设置较大时，轨迹会更加平滑；确保最小速度*sim_period （ minimum velocity × sim_period）小于我目的地容忍度的两倍！否则机器人会更倾向于在目标位置外原地旋转而不是到达目标点
（8）准确的轨迹simulation 也取决于合理的里程计的速度反馈估计，加速度限制和反馈速度决定了一个规划周期内合理的速度采样空间！
