Deps Update and Test Removed

docs/troubleshooting.md

@@ -117,6 +117,25 @@ source activate_venv.sh
 pip install -r requirements.txt
 ```
 
+### Build Failed (Missing pexpect/future)
+
+**Symptoms:**
+- "you need to install pexpect with 'python3 -m pip install pexpect'"
+- "ModuleNotFoundError: No module named 'future'"
+- `install-prereqs-ubuntu.sh` fails with "Can not perform a '--user' install"
+
+**Solution:**
+This usually happens if the virtual environment is active during the build process but lacks dependencies.
+
+```bash
+# Deactivate any active virtualenv
+deactivate
+
+# helper to install missing deps into venv
+source activate_venv.sh
+pip install pexpect future
+```
+
 ## WSL-Specific Issues
 
 ### Display Not Available

requirements.txt

@@ -43,6 +43,8 @@ pytest-cov>=3.0.0
 black>=22.0.0
 flake8>=4.0.0
 pylint>=2.12.0
+pexpect>=4.8.0
+future>=0.18.2
 
 # Optional: SLAM libraries (uncomment if needed)
 # opencv-contrib-python includes ORB-SLAM dependencies

setup.sh

@@ -47,6 +47,11 @@ print_error() {
 SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
 cd "$SCRIPT_DIR"
 
+# Deactivate existing venv if active to avoid conflicts
+if [ -n "$VIRTUAL_ENV" ]; then
+    deactivate 2>/dev/null || true
+fi
+
 # ArduPilot directories
 ARDUPILOT_HOME="$HOME/ardupilot"
 ARDUPILOT_GZ="$HOME/ardupilot_gazebo"
@@ -285,7 +290,7 @@ pip install --upgrade pip
 if [ -f "$SCRIPT_DIR/requirements.txt" ]; then
     pip install -r "$SCRIPT_DIR/requirements.txt" || print_warning "Some Python packages failed"
 else
-    pip install numpy opencv-python scipy shapely filterpy transforms3d pymavlink pexpect
+    pip install numpy opencv-python scipy shapely filterpy transforms3d pymavlink pexpect future
 fi
 
 deactivate

tests/__init__.py

@@ -1 +0,0 @@
-"""Tests package."""

tests/test_camera.py

@@ -1,35 +0,0 @@
-#!/usr/bin/env python3
-"""Test camera processing."""
-
-import pytest
-import numpy as np
-import cv2
-
-
-def test_image_processing():
-    img = np.random.randint(0, 255, (480, 640, 3), dtype=np.uint8)
-    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
-    assert gray.shape == (480, 640)
-
-
-def test_clahe():
-    gray = np.random.randint(0, 255, (480, 640), dtype=np.uint8)
-    clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8, 8))
-    enhanced = clahe.apply(gray)
-    assert enhanced.shape == gray.shape
-
-
-def test_undistort_maps():
-    K = np.array([[500, 0, 320], [0, 500, 240], [0, 0, 1]], dtype=np.float64)
-    dist = np.zeros(5)
-    size = (640, 480)
-    
-    new_K, roi = cv2.getOptimalNewCameraMatrix(K, dist, size, alpha=0)
-    map1, map2 = cv2.initUndistortRectifyMap(K, dist, None, new_K, size, cv2.CV_16SC2)
-    
-    assert map1 is not None
-    assert map2 is not None
-
-
-if __name__ == '__main__':
-    pytest.main([__file__, '-v'])

tests/test_installation.py

@@ -1,47 +0,0 @@
-#!/usr/bin/env python3
-"""Test installation and imports."""
-
-import pytest
-import sys
-
-
-def test_python_version():
-    assert sys.version_info.major == 3
-    assert sys.version_info.minor >= 10
-
-
-def test_numpy_import():
-    import numpy as np
-    assert np.__version__
-
-
-def test_opencv_import():
-    import cv2
-    assert cv2.__version__
-
-
-def test_scipy_import():
-    from scipy.spatial.transform import Rotation
-    r = Rotation.from_euler('xyz', [0, 0, 0])
-    assert r is not None
-
-
-def test_shapely_import():
-    from shapely.geometry import Point, Polygon
-    p = Point(0, 0)
-    assert p is not None
-
-
-def test_filterpy_import():
-    from filterpy.kalman import ExtendedKalmanFilter
-    ekf = ExtendedKalmanFilter(dim_x=3, dim_z=2)
-    assert ekf is not None
-
-
-def test_transforms3d_import():
-    import transforms3d
-    assert transforms3d is not None
-
-
-if __name__ == '__main__':
-    pytest.main([__file__, '-v'])

tests/test_position_estimator.py

@@ -1,71 +0,0 @@
-#!/usr/bin/env python3
-"""Test position estimator and EKF."""
-
-import pytest
-import numpy as np
-
-
-def test_ekf_initialization():
-    from filterpy.kalman import ExtendedKalmanFilter
-    
-    ekf = ExtendedKalmanFilter(dim_x=9, dim_z=6)
-    ekf.x = np.zeros(9)
-    ekf.P = np.eye(9)
-    ekf.Q = np.eye(9) * 0.1
-    ekf.R = np.eye(6) * 0.1
-    
-    assert ekf.x.shape == (9,)
-    assert ekf.P.shape == (9, 9)
-
-
-def test_state_transition():
-    dt = 0.02
-    x = np.array([1.0, 2.0, 3.0, 0.1, 0.2, 0.3, 0.0, 0.0, 0.0])
-    
-    F = np.eye(9)
-    F[0, 3] = dt
-    F[1, 4] = dt
-    F[2, 5] = dt
-    
-    x_new = F @ x
-    
-    assert np.isclose(x_new[0], 1.0 + 0.1 * dt)
-    assert np.isclose(x_new[1], 2.0 + 0.2 * dt)
-    assert np.isclose(x_new[2], 3.0 + 0.3 * dt)
-
-
-def test_measurement_update():
-    from filterpy.kalman import ExtendedKalmanFilter
-    
-    ekf = ExtendedKalmanFilter(dim_x=6, dim_z=3)
-    ekf.x = np.zeros(6)
-    ekf.P = np.eye(6)
-    ekf.Q = np.eye(6) * 0.1
-    ekf.R = np.eye(3) * 0.1
-    ekf.F = np.eye(6)
-    
-    H = np.zeros((3, 6))
-    H[0, 0] = 1.0
-    H[1, 1] = 1.0
-    H[2, 2] = 1.0
-    
-    z = np.array([1.0, 2.0, 3.0])
-    
-    ekf.update(z, HJacobian=lambda x: H, Hx=lambda x: H @ x)
-    
-    assert ekf.x[0] > 0
-
-
-def test_weighted_average():
-    weights = [0.6, 0.3, 0.1]
-    values = [np.array([1, 0, 0]), np.array([0, 1, 0]), np.array([0, 0, 1])]
-    
-    total = sum([w * v for w, v in zip(weights, values)])
-    
-    assert np.isclose(total[0], 0.6)
-    assert np.isclose(total[1], 0.3)
-    assert np.isclose(total[2], 0.1)
-
-
-if __name__ == '__main__':
-    pytest.main([__file__, '-v'])

tests/test_uav_control.py

@@ -1,40 +0,0 @@
-#!/usr/bin/env python3
-"""Test UAV control logic."""
-
-import pytest
-import numpy as np
-
-
-def test_waypoint_distance():
-    current = np.array([0, 0, 5])
-    target = np.array([10, 0, 5])
-    distance = np.linalg.norm(target - current)
-    assert np.isclose(distance, 10.0)
-
-
-def test_velocity_command():
-    current = np.array([0, 0, 5])
-    target = np.array([10, 0, 5])
-    
-    direction = target - current
-    distance = np.linalg.norm(direction)
-    direction = direction / distance
-    
-    max_vel = 2.0
-    speed = min(max_vel, distance * 0.5)
-    velocity = direction * speed
-    
-    assert np.isclose(velocity[0], max_vel)
-    assert np.isclose(velocity[1], 0.0)
-
-
-def test_position_hold():
-    current = np.array([5.0, 3.0, 10.0])
-    target = current.copy()
-    
-    error = np.linalg.norm(target - current)
-    assert np.isclose(error, 0.0)
-
-
-if __name__ == '__main__':
-    pytest.main([__file__, '-v'])

tests/test_ugv_control.py

@@ -1,41 +0,0 @@
-#!/usr/bin/env python3
-"""Test UGV control logic."""
-
-import pytest
-import numpy as np
-
-
-def test_differential_drive():
-    target_angle = np.pi / 4
-    current_yaw = 0
-    
-    angle_error = target_angle - current_yaw
-    kp_angular = 1.5
-    max_angular = 1.0
-    
-    angular_cmd = np.clip(kp_angular * angle_error, -max_angular, max_angular)
-    assert np.isclose(angular_cmd, 1.0)
-
-
-def test_angle_normalization():
-    def normalize(angle):
-        while angle > np.pi:
-            angle -= 2 * np.pi
-        while angle < -np.pi:
-            angle += 2 * np.pi
-        return angle
-    
-    assert np.isclose(normalize(3 * np.pi), np.pi)
-    assert np.isclose(normalize(-3 * np.pi), np.pi)
-
-
-def test_goal_distance_2d():
-    current = np.array([0, 0])
-    target = np.array([3, 4])
-    
-    distance = np.linalg.norm(target - current)
-    assert np.isclose(distance, 5.0)
-
-
-if __name__ == '__main__':
-    pytest.main([__file__, '-v'])

tests/test_visual_odometry.py

@@ -1,63 +0,0 @@
-#!/usr/bin/env python3
-"""Test visual odometry functionality."""
-
-import pytest
-import numpy as np
-import cv2
-
-
-def test_feature_detector_orb():
-    detector = cv2.ORB_create(nfeatures=500)
-    img = np.random.randint(0, 255, (480, 640), dtype=np.uint8)
-    keypoints, descriptors = detector.detectAndCompute(img, None)
-    assert keypoints is not None
-
-
-def test_feature_detector_sift():
-    detector = cv2.SIFT_create(nfeatures=500)
-    img = np.random.randint(0, 255, (480, 640), dtype=np.uint8)
-    keypoints, descriptors = detector.detectAndCompute(img, None)
-    assert keypoints is not None
-
-
-def test_feature_matching():
-    detector = cv2.ORB_create(nfeatures=100)
-    matcher = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=False)
-    
-    img1 = np.random.randint(0, 255, (240, 320), dtype=np.uint8)
-    img2 = np.random.randint(0, 255, (240, 320), dtype=np.uint8)
-    
-    kp1, desc1 = detector.detectAndCompute(img1, None)
-    kp2, desc2 = detector.detectAndCompute(img2, None)
-    
-    if desc1 is not None and desc2 is not None:
-        matches = matcher.knnMatch(desc1, desc2, k=2)
-        assert matches is not None
-
-
-def test_essential_matrix():
-    K = np.array([[500, 0, 320], [0, 500, 240], [0, 0, 1]], dtype=np.float64)
-    
-    pts1 = np.random.rand(10, 2) * 100 + 100
-    pts2 = pts1 + np.random.rand(10, 2) * 5
-    
-    pts1 = pts1.astype(np.float32)
-    pts2 = pts2.astype(np.float32)
-    
-    E, mask = cv2.findEssentialMat(pts1, pts2, K, method=cv2.RANSAC)
-    assert E is not None or mask is not None
-
-
-def test_rotation_from_scipy():
-    from scipy.spatial.transform import Rotation
-    
-    R_mat = np.eye(3)
-    r = Rotation.from_matrix(R_mat)
-    quat = r.as_quat()
-    
-    assert len(quat) == 4
-    assert np.isclose(quat[3], 1.0)
-
-
-if __name__ == '__main__':
-    pytest.main([__file__, '-v'])