yoi-hibino

#include <trajectory_msgs/msg/joint_trajectory.h>

rcl_subscription_t subscriber;
trajectory_msgs__msg__JointTrajectory traj_msg;
std::vector<TrajectoryPoint> points;

void traj_callback(const void *msgin) {
  const trajectory_msgs__msg__JointTrajectory *msg = (const trajectory_msgs__msg__JointTrajectory *)msgin;

  // TrajectoryPointsの受信処理

yoi-hibino

# spray_path_planner.py
import rclpy
from rclpy.node import Node
import pyrealsense2 as rs
import open3d as o3d
import numpy as np
import tf_transformations

from moveit_commander import RobotCommander, MoveGroupCommander
from geometry_msgs.msg import PoseStamped

yoi-hibino

from huggingface_hub import hf_hub_download
from huggingface_hub import login
from generator import load_csm_1b
import torchaudio
import sounddevice as sd
import numpy as np
from openai import OpenAI
import os

login("__your_huggingface_access_token_here__")

yoi-hibino

import numpy as np
import open3d as o3d
import transforms3d as t3d
import trimesh
import scipy.spatial
from sklearn.neighbors import KDTree
import time
import threading
import queue
import concurrent.futures

yoi-hibino

import numpy as np
import open3d as o3d
import matplotlib.pyplot as plt
import transforms3d as t3d
import trimesh
import scipy.spatial

class SensorLocalizer:
    def __init__(self, cad_model_path, scale_factor=1.0):
        """

yoi-hibino

from huggingface_hub import hf_hub_download
from generator import load_csm_1b
import torchaudio

# need this to access to model. 
# you also need to get access to https://huggingface.co/meta-llama/Llama-3.2-1B
from huggingface_hub import login
login("your_huggingface_token")

model_path = hf_hub_download(repo_id="sesame/csm-1b", filename="ckpt.pt")

yoi-hibino

#include <Wire.h>
#include <Arduino.h>

// Define number of IMUs and EKF parameters
#define NUM_IMUS 3  // Number of IMU sensors
#define EKF_N 10    // State vector dimension: [position (3), velocity (3), quaternion (4)]
#define EKF_M 9     // Measurement vector dimension: [accelerometer (3), gyroscope (3), magnetometer (3)]

// Include TinyEKF and set dimensions
#define EKF_N 10

yoi-hibino

import cv2
import numpy as np
import matplotlib.pyplot as plt

cap = cv2.VideoCapture('video.mp4')

ret, prev_frame = cap.read()
if not ret:
    raise ValueError("Could not read video.")
prev_gray = cv2.cvtColor(prev_frame, cv2.COLOR_BGR2GRAY)

yoi-hibino

import numpy as np
from filterpy.kalman import ExtendedKalmanFilter

# Assume our state vector x includes only position for simplicity.
# In practice, it would include orientation, velocity, etc.
# Let’s say x[0:3] is the "true" position of the reference point.

# Known sensor offset relative to the reference point
sensor_offset = np.array([0.1, -0.05, 0.0])  # in meters

yoi-hibino

import matplotlib.pyplot as plt
import numpy as np
import cv2


NACA_0018 =[[1.0000, 0.00000],
            [0.9500, 0.01210],
            [0.9000, 0.02172],
            [0.8000, 0.03935],
            [0.7000, 0.05496],