I think my code works correctly but the gradebot is failing .
This is the feedback :
[00:00:04] [warn] Grading has taken longer than expected. Aborting…
Things you can check:
Please try again and contact us if the problem persists. (mark: 4.0)
Hi Mohamed, I have exactly the same problem as you.
Hi @MohamedAliZouari and @nathan2000 post your code so we can see if it is correct or not. We receive many comments of students indicating that their code works but it is the gradebot that is failing. Usually the reason is that the student did not follow exactly the rules of the exercise (like names for functions, nodes, packages…) You need to follow the structure otherwise the gradebot will not properly grade your exercise. Let me remind you that being able to follow the instructions is an important skill for working in robotics, since nowadays nobody can work on his own to develop good robotics products
I have the same issue as well
#!/usr/bin/env python3
import rclpy
from rclpy.node import Node
from rclpy.qos import QoSProfile, ReliabilityPolicy
from sensor_msgs.msg import LaserScan
from geometry_msgs.msg import Twist
from nav_msgs.msg import Odometry
from std_msgs.msg import String
import math
import tf_transformations
class TopicsQuizNode(Node):
def init(self):
super().init(‘topics_quiz_node’)
# Subscribers
self.create_subscription(LaserScan, '/laser_scan', self.laserscan_callback, QoSProfile(depth=10, reliability=ReliabilityPolicy.RELIABLE))
self.create_subscription(Odometry, '/odom', self.odom_callback, QoSProfile(depth=10, reliability=ReliabilityPolicy.RELIABLE))
self.create_subscription(String, '/nasa_mission', self.mission_callback, 10)
# Publisher
self.publisher_ = self.create_publisher(Twist, '/cmd_vel', 10)
# Internal state
self.turning = False
self.turn_direction = -0.5
self.distance_from_origin = 0.0
self.current_position = {'x': 0.0, 'y': 0.0}
self.yaw = 0.0
# Mission control
self.mission_active = False
self.mission_type = None # 'go_home' or 'go_pickup'
self.pickup_point = {'x': -2.342, 'y': -2.432}
self.home_point = {'x': 0, 'y': 0}
self.get_logger().info("Waiting for mission command on /nasa_mission...")
def mission_callback(self, msg: String):
if msg.data == 'Go-Home':
self.mission_active = True
self.mission_type = 'go_home'
self.get_logger().info('Received Go-Home command.')
elif msg.data == 'Go-Pickup':
self.mission_active = True
self.mission_type = 'go_pickup'
self.get_logger().info('Received Go-Pickup command.')
def laserscan_callback(self, msg: LaserScan):
if not self.mission_active:
return # Ignore laser data unless a mission is active
if self.mission_type not in ['go_home', 'go_pickup']:
return
if self.mission_type == 'go_home' and self.distance_from_origin > 5.0:
self.navigate_to_target({'x': 0.0, 'y': 0.0})
return
if self.mission_type == 'go_pickup' and self.distance_to_point(self.pickup_point) > 0.5:
self.navigate_to_target(self.pickup_point)
return
# If at target, stop
if self.at_target():
self.get_logger().info("Target reached. Stopping.")
self.stop_motion()
self.mission_active = False
self.mission_type = None
return
# If navigating, avoid obstacles
self.avoid_obstacles(msg)
def odom_callback(self, msg: Odometry):
self.current_position['x'] = msg.pose.pose.position.x
self.current_position['y'] = msg.pose.pose.position.y
self.distance_from_origin = self.distance_to_point({'x': 0.0, 'y': 0.0})
orientation_q = msg.pose.pose.orientation
orientation_list = [orientation_q.x, orientation_q.y, orientation_q.z, orientation_q.w]
(roll, pitch, self.yaw) = tf_transformations.euler_from_quaternion(orientation_list)
def distance_to_point(self, point):
dx = point['x'] - self.current_position['x']
dy = point['y'] - self.current_position['y']
return math.sqrt(dx**2 + dy**2)
def at_target(self):
if self.mission_type == 'go_home':
return self.distance_from_origin <= 0.5
elif self.mission_type == 'go_pickup':
return self.distance_to_point(self.pickup_point) <= 0.5
return False
def is_at_position(self, target_position):
"""Check if the robot is within the tolerance of a target position."""
distance_to_target = math.sqrt(
(self.current_position['x'] - target_position['x'])**2 +
(self.current_position['y'] - target_position['y'])**2
)
return distance_to_target < 0.5
def navigate_to_target(self, target):
action = Twist()
dx = target['x'] - self.current_position['x']
dy = target['y'] - self.current_position['y']
target_yaw = math.atan2(dy, dx)
yaw_error = target_yaw - self.yaw
yaw_error = (yaw_error + math.pi) % (2 * math.pi) - math.pi # normalize
if abs(yaw_error) > 0.1:
action.angular.z = 0.5 if yaw_error > 0 else -0.5
self.get_logger().info(f"Rotating to target: yaw error {yaw_error:.2f}")
else:
action.linear.x = 0.5
self.get_logger().info("Moving toward target...")
self.publisher_.publish(action)
def avoid_obstacles(self, msg: LaserScan):
# Sector scan
sectors = {
"Right": msg.ranges[0:60],
"Front": msg.ranges[70:110],
"Left": msg.ranges[120:180]
}
front_min = min(sectors["Front"]) if sectors["Front"] else float('inf')
left_min = min(sectors["Left"]) if sectors["Left"] else float('inf')
right_min = min(sectors["Right"]) if sectors["Right"] else float('inf')
action = Twist()
if front_min < 0.8:
action.angular.z = 0.5
self.get_logger().info("Obstacle ahead, turning.")
elif left_min < 0.5:
action.angular.z = -0.3
elif right_min < 0.5:
action.angular.z = 0.3
else:
action.linear.x = 0.3
self.publisher_.publish(action)
def stop_motion(self):
stop_msg = Twist()
self.publisher_.publish(stop_msg)
def main(args=None):
rclpy.init(args=args)
node = TopicsQuizNode()
rclpy.spin_once(node)
if not node.is_at_position(node.home_point) and not node.is_at_position(node.pickup_point):
node.get_logger().info("Initial position not at home or pickup. Moving to home position.")
node.mission_type = 'go_home'
node.mission_active = True
rclpy.spin(node)
node.destroy_node()
rclpy.shutdown()
if name == ‘main’:
main()
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