latest pushes

Package/python/src/bellande_limit/__init__.py

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+"""
+ros_extension
+"""

Package/python/src/bellande_limit/bellande_limit_api.py

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+# Copyright (C) 2024 Bellande Robotics Sensors Research Innovation Center, Ronaldson Bellande
+
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 3 of the License, or
+# (at your option) any later version.
+
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+
+# You should have received a copy of the GNU General Public License
+# along with this program.  If not, see <https://www.gnu.org/licenses/>.
+
+#!/usr/bin/env python3
+
+import requests
+import argparse
+import json
+import sys
+
+def make_bellande_limit_request(node0, node1, environment, size, goal, obstacles=None, search_radius=50, sample_points=20):
+    url = "https://bellande-robotics-sensors-research-innovation-center.org/api/Bellande_Limit/bellande_limit"
+    
+    # Convert string inputs to lists if they're strings
+    if isinstance(node0, str):
+        node0 = json.loads(node0)
+    if isinstance(node1, str):
+        node1 = json.loads(node1)
+    if isinstance(environment, str):
+        environment = json.loads(environment)
+    if isinstance(size, str):
+        size = json.loads(size)
+    if isinstance(goal, str):
+        goal = json.loads(goal)
+    if isinstance(obstacles, str):
+        obstacles = json.loads(obstacles)
+        
+    payload = {
+        "node0": node0,
+        "node1": node1,
+        "environment": environment,
+        "size": size,
+        "goal": goal,
+        "obstacles": obstacles or [],
+        "search_radius": search_radius,
+        "sample_points": sample_points,
+        "auth": {
+            "authorization_key": "bellande_web_api_opensource"
+        }
+    }
+    
+    headers = {
+        'accept': 'application/json',
+        'Content-Type': 'application/json'
+    }
+    
+    try:
+        response = requests.post(url, json=payload, headers=headers)
+        response.raise_for_status()
+        return response.json()
+    except requests.RequestException as e:
+        print(f"Error making request: {e}", file=sys.stderr)
+        sys.exit(1)
+
+def main():
+    parser = argparse.ArgumentParser(description="Run Bellande Limit API")
+    parser.add_argument("--node0", required=True, help="Starting point coordinates as JSON-formatted list")
+    parser.add_argument("--node1", required=True, help="Target point coordinates as JSON-formatted list")
+    parser.add_argument("--environment", required=True, help="Environment dimensions as JSON-formatted list")
+    parser.add_argument("--size", required=True, help="Step sizes for each dimension as JSON-formatted list")
+    parser.add_argument("--goal", required=True, help="Goal coordinates as JSON-formatted list")
+    parser.add_argument("--obstacles", help="List of obstacles as JSON-formatted list of objects with 'position' and 'dimensions'")
+    parser.add_argument("--search-radius", type=float, default=50.0, help="Search radius for obstacle detection")
+    parser.add_argument("--sample-points", type=int, default=20, help="Number of sample points for obstacle detection")
+    
+    args = parser.parse_args()
+    
+    try:
+        result = make_bellande_limit_request(
+            args.node0,
+            args.node1,
+            args.environment,
+            args.size,
+            args.goal,
+            args.obstacles,
+            args.search_radius,
+            args.sample_points
+        )
+        
+        print(json.dumps(result, indent=2))
+    except json.JSONDecodeError as e:
+        print(f"Error: Invalid JSON format in input parameters - {e}", file=sys.stderr)
+        sys.exit(1)
+
+if __name__ == "__main__":
+    main()

Package/python/src/bellande_limit/bellande_limit_executable.py

@@ -0,0 +1,101 @@
+# Copyright (C) 2024 Bellande Robotics Sensors Research Innovation Center, Ronaldson Bellande
+
+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 3 of the License, or
+# (at your option) any later version.
+
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+
+# You should have received a copy of the GNU General Public License
+# along with this program.  If not, see <https://www.gnu.org/licenses/>.
+
+#!/usr/bin/env python3
+
+import subprocess
+import argparse
+import json
+import os
+import sys
+
+def get_executable_path():
+    if getattr(sys, 'frozen', False):
+        application_path = sys._MEIPASS
+    else:
+        application_path = os.path.dirname(os.path.abspath(__file__))
+    
+    return os.path.join(application_path, 'Bellande_Limit')
+
+def run_bellande_limit(node0, node1, environment, size, goal, obstacles=None, search_radius=50, sample_points=20):
+    executable_path = get_executable_path()
+    passcode = "bellande_limit_executable_access_key"
+    
+    # Convert string representations to actual lists/objects
+    node0_list = json.loads(node0)
+    node1_list = json.loads(node1)
+    environment_list = json.loads(environment)
+    size_list = json.loads(size)
+    goal_list = json.loads(goal)
+    obstacles_list = json.loads(obstacles) if obstacles else []
+    
+    # Validate input dimensions
+    dimensions = len(environment_list)
+    if not all(len(x) == dimensions for x in [node0_list, node1_list, size_list, goal_list]):
+        raise ValueError(f"All coordinates must have {dimensions} dimensions")
+    
+    # Validate obstacles
+    for obstacle in obstacles_list:
+        if len(obstacle['position']) != dimensions or len(obstacle['dimensions']) != dimensions:
+            raise ValueError(f"Obstacle position and dimensions must have {dimensions} dimensions")
+    
+    # Prepare the command
+    command = [
+        executable_path,
+        passcode,
+        json.dumps(node0_list),
+        json.dumps(node1_list),
+        json.dumps(environment_list),
+        json.dumps(size_list),
+        json.dumps(goal_list),
+        json.dumps(obstacles_list),
+        str(search_radius),
+        str(sample_points)
+    ]
+    
+    # Run the command
+    try:
+        result = subprocess.run(command, check=True, capture_output=True, text=True)
+        print(result.stdout)
+    except subprocess.CalledProcessError as e:
+        print("Error occurred:", e)
+        print("Error output:", e.stderr)
+
+def main():
+    parser = argparse.ArgumentParser(description="Run Bellande Limit Executable")
+    parser.add_argument("--node0", required=True, help="Starting point coordinates as JSON-formatted list")
+    parser.add_argument("--node1", required=True, help="Target point coordinates as JSON-formatted list")
+    parser.add_argument("--environment", required=True, help="Environment dimensions as JSON-formatted list")
+    parser.add_argument("--size", required=True, help="Step sizes for each dimension as JSON-formatted list")
+    parser.add_argument("--goal", required=True, help="Goal coordinates as JSON-formatted list")
+    parser.add_argument("--obstacles", help="List of obstacles as JSON-formatted list of objects with 'position' and 'dimensions'")
+    parser.add_argument("--search-radius", type=float, default=50.0, help="Search radius for obstacle detection")
+    parser.add_argument("--sample-points", type=int, default=20, help="Number of sample points for obstacle detection")
+    
+    args = parser.parse_args()
+    
+    run_bellande_limit(
+        args.node0,
+        args.node1,
+        args.environment,
+        args.size,
+        args.goal,
+        args.obstacles,
+        args.search_radius,
+        args.sample_points
+    )
+
+if __name__ == "__main__":
+    main()