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Showing SKILL.md
| name | localization |
| description | 四足机器人定位 - SLAM建图、IMU融合、EKF定位、UWB定位 |
| argument-hint | 四足定位 OR SLAM OR IMU融合 OR 定位 |
| user-invocable | true |
用于配置和开发四足机器人的定位系统
当需要以下帮助时使用此技能：
| 框架 | 特点 | 适用场景 |
|---|---|---|
| cartographer | 闭环检测、submap | 室内建图 |
| gmapping | 粒子滤波 | 小范围建图 |
| karto | 稀疏调整 | 中等范围 |
| RTAB-Map | 外观匹配 | 大范围 |
| LIO-SAM | 激光+IMU | 室外 |
# 启动 cartographer
ros2 launch cartographer_ros cartographer.launch.py \
configuration_basename:=lantern.lua \
robot_description:=robot.urdf
-- lantern.lua
TRAJECTORY_BUILDER_2D.scans_per_accumulation = 1
POSE_GRAPH.optimize_every_n_nodes = 90
ros2 launch slam_toolbox online_async_launch.py \
slam_params_file:=params.yaml
ekf_filter:
frequency: 50
odom0: /odom
odom1: /imu
imu0: /imu/data
process_noise_cov: [0.05, 0, 0, 0, 0, 0, 0, 0.05, 0, 0, 0, 0, 0, 0, 0.05, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
ros2 launch robot_localization ekf.launch.py \
odometry:=ekf_odom \
config_file:=ekf.yaml
ros2 launch rtabmap rtabmap.launch.py \
rgbd_sync:=true \
scan_cloud_topic:=/scan \
odom_topic:=/odom
vio:
provider: rtabmap / vins-fusion / okvis
camera:
topics: [/camera/left/image, /camera/right/image]
baseline: 0.12
# NMEA GPS
ros2 run nmea_navsat_driver nmea_serial_node \
port:=/dev/gps \
baud:=115200
rtk:
type: ublox / septentrio
corrections:
type: NTRIP
caster: rtk.example.com
port: 2101
mountpoint: RTS0
username: user
password: pass
def compute_relative_pose(pose1, pose2):
"""计算两个机器人间的相对位姿"""
delta_x = pose2.x - pose1.x
delta_y = pose2.y - pose1.y
delta_theta = pose2.theta - pose1.theta
return (delta_x, delta_y, delta_theta)
| 包 | 功能 |
|---|---|
cartographer_ros | cartographer SLAM |
slam_toolbox | 同步定位建图 |
robot_localization | EKF 融合 |
rtabmap_ros | 视觉 SLAM |
nmea_navsat_driver | GPS 驱动 |