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steal_pantry

StealPantryAction #

Bases: Action

Action used to steal crates from a pantry.

Source code in cogip/tools/planner/actions/steal_pantry.py
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class StealPantryAction(Action):
    """
    Action used to steal crates from a pantry.
    """

    def __init__(
        self,
        planner: "Planner",
        strategy: Strategy,
        pantry_id: PantryID,
        weight: float = 2000000.0,
    ):
        self.custom_weight = weight
        super().__init__(f"StealPantry {pantry_id.name}", planner, strategy)
        self.before_action_func = self.before_action
        self.pantry_id = pantry_id
        self.shift_inspect = 350
        self.shift_align = 150
        self.shift_capture = self.shift_align + 15
        self.shift_approach = self.shift_align + 160
        self.shift_step_back = 70
        if Camp().color == Camp.Colors.blue:
            self.good_crate_id = 36
            self.bad_crate_id = 47
        else:
            self.good_crate_id = 47
            self.bad_crate_id = 36
        self.crate_group: CrateGroup | None = None

    @property
    def pantry(self) -> Pantry:
        return self.planner.game_context.pantries[self.pantry_id]

    async def recycle(self):
        self.pantry.enabled = self.pantry_enabled_backup
        self.recycled = True

    async def before_action(self):
        self.logger.info(f"{self.name}: before_action")
        self.poses.clear()
        self.crate_group: CrateGroup | None = None
        self.pantry_enabled_backup = self.pantry.enabled
        self.pantry.enabled = False

        if self.planner.game_context.front_free:
            self.side = "front"
            self.crates_ids = self.planner.game_context.front_crates
            self.arms_open = functools.partial(actuators.front_arms_open, self.planner)
            self.arms_close = functools.partial(actuators.front_arms_close, self.planner)
            self.lift_down = functools.partial(actuators.front_lift_down, self.planner)
            self.lift_mid = functools.partial(actuators.front_lift_mid, self.planner)
        else:
            self.side = "back"
            self.crates_ids = self.planner.game_context.back_crates
            self.arms_open = functools.partial(actuators.back_arms_open, self.planner)
            self.arms_close = functools.partial(actuators.back_arms_close, self.planner)
            self.lift_down = functools.partial(actuators.back_lift_down, self.planner)
            self.lift_mid = functools.partial(actuators.back_lift_mid, self.planner)

        x, y = crates_utils.shift_pantry_center_from_border(self.pantry)
        self.inspect_pose = Pose(
            x=x,
            y=y,
            O=0,
            max_speed_linear=100,
            max_speed_angular=100,
            motion_direction=MotionDirection.BIDIRECTIONAL,
            bypass_final_orientation=False,
            stop_before_distance=self.shift_inspect,
            before_pose_func=self.before_inspect_pose,
            after_pose_func=self.after_inspect_pose,
        )
        self.poses.append(self.inspect_pose)

    async def before_inspect_pose(self):
        self.logger.info(f"{self.name}: before_inspect_pose")
        if self.planner.game_context.front_free:
            await actuators.front_arms_close(self.planner)
            await actuators.front_lift_mid(self.planner)
        if self.planner.game_context.back_free:
            await actuators.back_arms_close(self.planner)
            await actuators.back_lift_mid(self.planner)

    async def after_inspect_pose(self):
        self.logger.info(f"{self.name}: after_inspect_pose")
        await asyncio.sleep(0.5)
        pose_current = self.planner.pose_current

        # Check orientation to pantry
        angle_to_pantry = math.degrees(math.atan2(self.pantry.y - pose_current.y, self.pantry.x - pose_current.x))
        angle_diff = angle_to_pantry - pose_current.O
        self.logger.info(
            f"{self.name}: angle to pantry: "
            f"{angle_to_pantry: 3.2f}°, current angle: {pose_current.O: 3.2f}°, diff: {angle_diff: 3.2f}°"
        )
        # Normalize to [-180, 180]
        while angle_diff > 180:
            angle_diff -= 360
        while angle_diff < -180:
            angle_diff += 360
        if abs(angle_diff) > 10:
            # Need to add an orientation adjustment pose
            self.logger.info(f"{self.name}: adding orientation adjustment pose (diff={angle_diff: 3.2f}°)")
            adjust_pose = Pose(
                x=pose_current.x,
                y=pose_current.y,
                O=angle_to_pantry,
                max_speed_linear=50,
                max_speed_angular=50,
                motion_direction=MotionDirection.BIDIRECTIONAL,
                bypass_final_orientation=False,
                before_pose_func=self.before_inspect_orientation,
                after_pose_func=self.after_inspect_orientation,
            )
            self.poses.append(adjust_pose)
        else:
            self.logger.info(f"{self.name}: orientation to pantry is acceptable (diff={angle_diff: 3.2f}°)")
            await self.after_inspect_orientation()

    async def before_inspect_orientation(self):
        self.logger.info(f"{self.name}: before_inspect_orientation")

    async def after_inspect_orientation(self):
        self.logger.info(f"{self.name}: after_inspect_orientation")
        await asyncio.sleep(0.5)
        pose_current = self.planner.pose_current
        crates_found: list[tuple[int, models.Pose]] = await get_crates_position(self.planner)
        self.logger.info(f"{self.name}: crates found:")
        for crate_id, pose in crates_found:
            self.logger.info(f"{self.name}: - {crate_id}: x={pose.x: 5.2f} y={pose.y: 5.2f} O={pose.O: 3.2f}°")

        # 1. Analyze crates to find valid groups
        analyzer = CrateAnalyzer(self.good_crate_id, self.bad_crate_id)
        valid_groups = analyzer.find_groups(crates_found)

        if not valid_groups:
            self.logger.warning(f"{self.name}: No valid crate group found")
            return

        for i, group in enumerate(valid_groups):
            self.logger.info(
                f"{self.name}: Group {i}: x={group.pose.x: 5.2f} y={group.pose.y: 5.2f} O={group.pose.O: 3.2f}°"
                f" IDs={group.crate_ids} BadCount={group.bad_crate_count}"
            )

        # 2. Select the best group that is reachable
        best_approach_pose: models.Pose | None = None

        for group in valid_groups:
            # Convert group_pose to table frame
            group_pose_table = transform_to_table_frame(group.pose, pose_current)

            self.logger.info(
                f"{self.name}: Testing group (table frame): "
                f"x={group_pose_table.x: 5.2f} y={group_pose_table.y: 5.2f} O={group_pose_table.O: 3.2f}°"
            )

            # Exclude groups too far from pantry
            dist_to_pantry = math.hypot(
                group_pose_table.x - self.pantry.x,
                group_pose_table.y - self.pantry.y,
            )
            if dist_to_pantry > 180:
                self.logger.info(f"{self.name}: Group too far from pantry (dist={dist_to_pantry:.0f}mm), skipping")
                continue

            # Update pantry state using crate group pose
            self.pantry.x = group_pose_table.x
            self.pantry.y = group_pose_table.y
            self.pantry.O = group_pose_table.O
            self.pantry.enabled = True

            # Compute possible approach positions
            front_approach_pose = get_relative_pose(
                group_pose_table,
                front_offset=-self.shift_approach,
                angular_offset=0,
            )
            back_approach_pose = get_relative_pose(
                group_pose_table,
                front_offset=self.shift_approach,
                angular_offset=180,
            )

            # Identify obstacle crates (transform to table frame)
            # A crate is part of the group if it is within 150mm of the group center (in robot frame)
            obstacle_crates_table: list[models.Pose] = []
            for _, crate_pose in crates_found:
                if crate_pose in group.crates:
                    continue
                obstacle_crates_table.append(transform_to_table_frame(crate_pose, pose_current))

            # Check reachability
            approach_pose = self.choose_approach_position(
                pose_current,
                front_approach_pose,
                back_approach_pose,
                group_pose_table,
                obstacle_crates_table,
            )

            if approach_pose:
                self.crate_group = group
                best_approach_pose = approach_pose
                self.logger.info(f"{self.name}: Found reachable group with approach: {approach_pose}")
                break
            else:
                self.logger.info(f"{self.name}: Group not reachable")

        if not self.crate_group:
            self.logger.warning(f"{self.name}: No reachable group found")
            return

        if self.crate_group.bad_crate_count == 0:
            self.logger.warning(f"{self.name}: Selected group has no bad crates, aborting steal")
            return

        self.crates_ids[:] = self.crate_group.crate_ids[:]

        # Create approach pose
        approach_pose = Pose(
            **best_approach_pose.model_dump(),
            max_speed_linear=10,
            max_speed_angular=10,
            motion_direction=MotionDirection.BIDIRECTIONAL,
            bypass_final_orientation=True,
            before_pose_func=self.before_approach,
            after_pose_func=self.after_approach,
        )
        self.poses.append(approach_pose)
        self.logger.info(
            f"{self.name}: approach: x={approach_pose.x: 5.2f} y={approach_pose.y: 5.2f} O={approach_pose.O: 3.2f}°"
        )

        # Align
        align_pose = Pose(
            **get_relative_pose(
                best_approach_pose,
                front_offset=self.shift_approach - self.shift_align,
                angular_offset=0,
            ).model_dump(),
            max_speed_linear=10,
            max_speed_angular=10,
            motion_direction=(
                MotionDirection.FORWARD_ONLY if self.planner.game_context.front_free else MotionDirection.BACKWARD_ONLY
            ),
            before_pose_func=self.before_align,
            after_pose_func=self.after_align,
        )
        self.poses.append(align_pose)
        self.logger.info(f"{self.name}: align: x={align_pose.x: 5.2f} y={align_pose.y: 5.2f} O={align_pose.O: 3.2f}°")

        # Capture
        capture_pose = Pose(
            **get_relative_pose(
                best_approach_pose,
                front_offset=self.shift_approach - self.shift_capture,
                angular_offset=0,
            ).model_dump(),
            max_speed_linear=10,
            max_speed_angular=10,
            motion_direction=(
                MotionDirection.BACKWARD_ONLY if self.planner.game_context.front_free else MotionDirection.FORWARD_ONLY
            ),
            bypass_final_orientation=True,
            before_pose_func=self.before_capture,
            after_pose_func=self.after_capture,
        )
        self.poses.append(capture_pose)
        self.logger.info(
            f"{self.name}: capture: x={capture_pose.x: 5.2f} y={capture_pose.y: 5.2f} O={capture_pose.O: 3.2f}°"
        )

    def choose_approach_position(
        self,
        pose_current: models.Pose,
        front_pose: models.Pose,
        back_pose: models.Pose,
        group_pose: models.Pose,
        obstacle_crates: list[models.Pose],
    ) -> models.Pose | None:
        """
        Choose the best approach position (front or back) based on distance to current pose.
        """
        valid_poses: list[models.Pose] = [front_pose, back_pose]

        # check if approach positions are within table bounds
        robot_width = self.planner.shared_properties.robot_width
        limits = self.planner.shared_table_limits.copy()
        limits[0] += robot_width / 2  # min x
        limits[1] -= robot_width / 2  # max x
        limits[2] += robot_width / 2  # min y
        limits[3] -= robot_width / 2  # max y
        for pose in valid_poses.copy():
            if not (limits[0] <= pose.x <= limits[1] and limits[2] <= pose.y <= limits[3]):
                self.logger.warning(
                    f"{self.name}: Approach position x={pose.x: 5.2f} y={pose.y: 5.2f}° out of table bounds"
                )
                valid_poses.remove(pose)

        if not valid_poses:
            self.logger.warning(f"{self.name}: No valid approach positions within table bounds")
            return None

        # Check if approach positions is not in an obstacle
        # and if the path between approach and capture pose is clear
        self.planner.shared_obstacles_lock.start_reading()
        for pose in valid_poses.copy():
            capture_pose = get_relative_pose(
                pose,
                front_offset=self.shift_approach - self.shift_capture,
                angular_offset=0,
            )

            # Check dynamic and static obstacles from planner
            is_valid = True
            for obstacle_list in [self.planner.shared_circle_obstacles, self.planner.shared_rectangle_obstacles]:
                obstacle_list: list[ObstacleCircle | ObstacleRectangle]
                for obstacle in obstacle_list:
                    if obstacle.is_point_inside(pose.x, pose.y):
                        self.logger.warning(
                            f"{self.name}: Approach position x={pose.x: 5.2f} y={pose.y: 5.2f} in obstacle"
                        )
                        is_valid = False
                        break
                    if obstacle.is_segment_crossing(pose.x, pose.y, capture_pose.x, capture_pose.y):
                        self.logger.warning(
                            f"{self.name}: Path from approach x={pose.x: 5.2f} y={pose.y: 5.2f}° "
                            f"to capture x={capture_pose.x: 5.2f} y={capture_pose.y: 5.2f}° intersects obstacle"
                        )
                        is_valid = False
                        break
                if not is_valid:
                    valid_poses.remove(pose)
                    break

            if not is_valid:
                continue

            # Check against other crates
            for crate_pose in obstacle_crates:
                obstacle = ObstacleRectangle(crate_pose.x, crate_pose.y, crate_pose.O, 160, 60, 0)
                if obstacle.is_point_inside(pose.x, pose.y):
                    self.logger.warning(
                        f"{self.name}: Approach position x={pose.x: 5.2f} y={pose.y: 5.2f}"
                        f" inside crate at x={crate_pose.x:.0f} y={crate_pose.y:.0f}"
                    )
                    is_valid = False
                    break
                if obstacle.is_segment_crossing(pose.x, pose.y, group_pose.x, group_pose.y):
                    self.logger.warning(
                        f"{self.name}: Approach path from x={pose.x: 5.2f} y={pose.y: 5.2f}"
                        f" to x={group_pose.x: 5.2f} y={group_pose.y: 5.2f} intersects crate"
                        f" at x={crate_pose.x:.0f} y={crate_pose.y:.0f}"
                    )
                    is_valid = False
                    break

            if not is_valid:
                valid_poses.remove(pose)

        self.planner.shared_obstacles_lock.finish_reading()

        if not valid_poses:
            self.logger.warning(f"{self.name}: No valid approach positions available")
            return None

        if len(valid_poses) == 1:
            self.logger.info(f"{self.name}: Only one valid approach position available")
            return valid_poses[0]

        # Select closest approach position
        dist_front = math.hypot(front_pose.x - pose_current.x, front_pose.y - pose_current.y)
        dist_back = math.hypot(back_pose.x - pose_current.x, back_pose.y - pose_current.y)

        if dist_front <= dist_back:
            self.logger.info(f"{self.name}: Chose front approach position (distance: {dist_front: 5.2f} mm)")
            return front_pose
        else:
            self.logger.info(f"{self.name}: Chose back approach position (distance: {dist_back: 5.2f} mm)")
            return back_pose

    async def before_approach(self):
        self.logger.info(f"{self.name}: before_approach")
        await self.arms_close()
        await self.lift_mid()

    async def after_approach(self):
        self.logger.info(f"{self.name}: after_approach")

    async def before_align(self):
        self.logger.info(f"{self.name}: before_align")
        self.pantry.enabled = False
        await self.lift_down()
        await self.arms_open()
        self.logger.info(f"{self.name}: before_align: end")

    async def after_align(self):
        self.logger.info(f"{self.name}: after_align")

    async def before_capture(self):
        self.logger.info(f"{self.name}: before_capture: begin")

    async def after_capture(self):
        self.logger.info(f"{self.name}: after_capture")
        await crates_utils.take_crates(self.planner, self.side)
        drop_pose = await crates_utils.drop_crates(self.planner, self.side)
        self.after_drop_org = drop_pose.after_pose_func
        drop_pose.after_pose_func = self.after_drop
        self.poses.append(drop_pose)

    async def after_drop(self):
        await self.after_drop_org()

        # Step back
        pose_current = self.pose_current
        shift_step_back = self.shift_step_back if self.side == "front" else -self.shift_step_back
        step_back_pose = Pose(
            **get_relative_pose(pose_current, front_offset=-shift_step_back).model_dump(),
            max_speed_linear=50,
            max_speed_angular=50,
            motion_direction=MotionDirection.BACKWARD_ONLY if self.side == "front" else MotionDirection.FORWARD_ONLY,
            bypass_final_orientation=True,
            before_pose_func=self.before_step_back,
            after_pose_func=self.after_step_back,
        )
        self.poses.append(step_back_pose)
        self.logger.info(
            f"{self.name}: step back: x={step_back_pose.x: 5.2f} y={step_back_pose.y: 5.2f} O={step_back_pose.O: 3.2f}°"
        )

    async def before_step_back(self):
        self.logger.info(f"{self.name}: before_step_back")

    async def after_step_back(self):
        self.logger.info(f"{self.name}: after_step_back")
        self.pantry.enabled = True

    def weight(self) -> float:
        if not self.planner.game_context.front_free and not self.planner.game_context.back_free:
            self.logger.info(f"{self.name}: Rejected: both front and back are full")
            return 0

        return self.custom_weight

choose_approach_position(pose_current, front_pose, back_pose, group_pose, obstacle_crates) #

Choose the best approach position (front or back) based on distance to current pose.

Source code in cogip/tools/planner/actions/steal_pantry.py
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def choose_approach_position(
    self,
    pose_current: models.Pose,
    front_pose: models.Pose,
    back_pose: models.Pose,
    group_pose: models.Pose,
    obstacle_crates: list[models.Pose],
) -> models.Pose | None:
    """
    Choose the best approach position (front or back) based on distance to current pose.
    """
    valid_poses: list[models.Pose] = [front_pose, back_pose]

    # check if approach positions are within table bounds
    robot_width = self.planner.shared_properties.robot_width
    limits = self.planner.shared_table_limits.copy()
    limits[0] += robot_width / 2  # min x
    limits[1] -= robot_width / 2  # max x
    limits[2] += robot_width / 2  # min y
    limits[3] -= robot_width / 2  # max y
    for pose in valid_poses.copy():
        if not (limits[0] <= pose.x <= limits[1] and limits[2] <= pose.y <= limits[3]):
            self.logger.warning(
                f"{self.name}: Approach position x={pose.x: 5.2f} y={pose.y: 5.2f}° out of table bounds"
            )
            valid_poses.remove(pose)

    if not valid_poses:
        self.logger.warning(f"{self.name}: No valid approach positions within table bounds")
        return None

    # Check if approach positions is not in an obstacle
    # and if the path between approach and capture pose is clear
    self.planner.shared_obstacles_lock.start_reading()
    for pose in valid_poses.copy():
        capture_pose = get_relative_pose(
            pose,
            front_offset=self.shift_approach - self.shift_capture,
            angular_offset=0,
        )

        # Check dynamic and static obstacles from planner
        is_valid = True
        for obstacle_list in [self.planner.shared_circle_obstacles, self.planner.shared_rectangle_obstacles]:
            obstacle_list: list[ObstacleCircle | ObstacleRectangle]
            for obstacle in obstacle_list:
                if obstacle.is_point_inside(pose.x, pose.y):
                    self.logger.warning(
                        f"{self.name}: Approach position x={pose.x: 5.2f} y={pose.y: 5.2f} in obstacle"
                    )
                    is_valid = False
                    break
                if obstacle.is_segment_crossing(pose.x, pose.y, capture_pose.x, capture_pose.y):
                    self.logger.warning(
                        f"{self.name}: Path from approach x={pose.x: 5.2f} y={pose.y: 5.2f}° "
                        f"to capture x={capture_pose.x: 5.2f} y={capture_pose.y: 5.2f}° intersects obstacle"
                    )
                    is_valid = False
                    break
            if not is_valid:
                valid_poses.remove(pose)
                break

        if not is_valid:
            continue

        # Check against other crates
        for crate_pose in obstacle_crates:
            obstacle = ObstacleRectangle(crate_pose.x, crate_pose.y, crate_pose.O, 160, 60, 0)
            if obstacle.is_point_inside(pose.x, pose.y):
                self.logger.warning(
                    f"{self.name}: Approach position x={pose.x: 5.2f} y={pose.y: 5.2f}"
                    f" inside crate at x={crate_pose.x:.0f} y={crate_pose.y:.0f}"
                )
                is_valid = False
                break
            if obstacle.is_segment_crossing(pose.x, pose.y, group_pose.x, group_pose.y):
                self.logger.warning(
                    f"{self.name}: Approach path from x={pose.x: 5.2f} y={pose.y: 5.2f}"
                    f" to x={group_pose.x: 5.2f} y={group_pose.y: 5.2f} intersects crate"
                    f" at x={crate_pose.x:.0f} y={crate_pose.y:.0f}"
                )
                is_valid = False
                break

        if not is_valid:
            valid_poses.remove(pose)

    self.planner.shared_obstacles_lock.finish_reading()

    if not valid_poses:
        self.logger.warning(f"{self.name}: No valid approach positions available")
        return None

    if len(valid_poses) == 1:
        self.logger.info(f"{self.name}: Only one valid approach position available")
        return valid_poses[0]

    # Select closest approach position
    dist_front = math.hypot(front_pose.x - pose_current.x, front_pose.y - pose_current.y)
    dist_back = math.hypot(back_pose.x - pose_current.x, back_pose.y - pose_current.y)

    if dist_front <= dist_back:
        self.logger.info(f"{self.name}: Chose front approach position (distance: {dist_front: 5.2f} mm)")
        return front_pose
    else:
        self.logger.info(f"{self.name}: Chose back approach position (distance: {dist_back: 5.2f} mm)")
        return back_pose

transform_to_table_frame(pose_robot_frame, robot_pose) #

Transform a pose from robot frame to table frame.

Source code in cogip/tools/planner/actions/steal_pantry.py
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def transform_to_table_frame(pose_robot_frame: models.Pose, robot_pose: models.Pose) -> models.Pose:
    """
    Transform a pose from robot frame to table frame.
    """
    rad_robot = math.radians(robot_pose.O)
    cos_robot = math.cos(rad_robot)
    sin_robot = math.sin(rad_robot)

    return models.Pose(
        x=robot_pose.x + pose_robot_frame.x * cos_robot - pose_robot_frame.y * sin_robot,
        y=robot_pose.y + pose_robot_frame.x * sin_robot + pose_robot_frame.y * cos_robot,
        O=robot_pose.O + pose_robot_frame.O,
    )