科沃斯x11pro的优缺点

核心亮点‌

‌顶级清洁性能‌

‌8000Pa超强吸力‌：轻松应对地毯深层灰尘、宠物毛发等顽固垃圾。

‌双旋转增压拖布‌：模拟人手加压擦地，配合60℃热水洗拖布，油污、咖啡渍等清洁效率提升30%。

‌动态贴边清洁2.0‌：沿边死角清洁距离缩至2mm，墙边、家具脚清洁更彻底。

‌智能导航与避障‌

‌AI视觉+3D结构光双避障‌：精准识别拖鞋、电线、宠物粪便等障碍物，减少卡困风险。

‌dToF激光雷达导航‌：建图速度提升40%，支持多层地图自动切换（如复式户型）。

科沃斯x11pro活动直降700机会不容错过 https://u.jd.com/ArfUaBY

‌全能基站体验‌

‌自动集尘+自动洗烘拖布‌：3L尘袋可支持75天免倒垃圾，热风烘干拖布避免发霉异味。

‌基站自清洁‌：一键清理基站污水槽，维护更省心。

‌交互便捷性‌

‌YIKO 2.0语音助手‌：支持"扫这里""避开餐桌"等复杂指令。

‌APP智能规划‌：可设置不同房间的清洁顺序、吸力/水量档位。

‌潜在不足‌

‌价格较高‌：首发价通常在5000元以上，适合预算充足的用户。

‌基站体积较大‌：需预留约40cm×50cm的摆放空间。

‌复杂场景局限性‌：极端杂乱环境（如满地玩具）仍需人工预整理。

‌适用场景推荐‌

‌大平层/复式户型‌：多层地图和长续航（约200㎡单次清洁）表现优秀。

‌有宠家庭‌：强吸力+热风除菌拖布，有效处理宠物毛发和异味。

‌追求"零动手"体验‌：从清洁到基站维护全自动化，解放用户。

代码

python 复制代码

class RoboticCleaner:
    def __init__(self):
        self.suction_power = 8000  # Pa
        self.mop_rotation_speed = 120  # RPM
        self.water_temp = 60  # ℃
        self.edge_cleaning_gap = 2  # mm

    def activate_deep_cleaning(self):
        """启用8000Pa吸力模式"""
        return f"Deep cleaning activated at {self.suction_power}Pa"

    def hot_water_mopping(self):
        """60℃热水洗拖布系统"""
        return f"Mopping with {self.water_temp}℃ hot water"

    def edge_cleaning_mode(self):
        """2mm贴边清洁"""
        return f"Edge cleaning with {self.edge_cleaning_gap}mm gap"

python 复制代码

class RoboticCleaner:
    def __init__(self):
        self.suction_power = 8000  # Pa
        self.mop_rotation_speed = 120  # RPM
        self.water_temp = 60  # ℃
        self.edge_cleaning_gap = 2  # mm

    def activate_deep_cleaning(self):
        """启用8000Pa吸力模式"""
        return f"Deep cleaning activated at {self.suction_power}Pa"

    def hot_water_mopping(self):
        """60℃热水洗拖布系统"""
        return f"Mopping with {self.water_temp}℃ hot water"

    def edge_cleaning_mode(self):
        """2mm贴边清洁"""
        return f"Edge cleaning with {self.edge_cleaning_gap}mm gap"

python 复制代码

class NavigationSystem:
    def __init__(self):
        self.obstacle_types = ["slippers", "wires", "pet_waste"]
        self.mapping_speed = "3x faster"
        self.floor_maps = {}

    def detect_obstacle(self, obj):
        """AI视觉+3D结构光避障"""
        if obj in self.obstacle_types:
            return f"Avoiding {obj} with 3D structured light"
        return "No obstacle detected"

    def multi_floor_mapping(self, floor_plan):
        """多层地图自动切换"""
        self.floor_maps.update(floor_plan)
        return f"{len(floor_plan)} floors mapped"

python 复制代码

class DockingStation:
    def __init__(self):
        self.dustbag_capacity = 75  # days
        self.auto_clean_interval = 24  # hours

    def auto_empty_dustbin(self):
        """75天自动集尘"""
        return f"Auto-emptying dustbin (lasts {self.dustbag_capacity} days)"

    def self_cleaning(self):
        """基站自清洁"""
        return "Cleaning wastewater tank"

python 复制代码

class VoiceControl:
    def __init__(self):
        self.commands = {
            "clean here": "spot_cleaning",
            "avoid table": "set_no_go_zone"
        }

    def process_command(self, voice_input):
        """YIKO 2.0语音助手"""
        for cmd, action in self.commands.items():
            if cmd in voice_input.lower():
                return f"Executing: {action}"
        return "Command not recognized"

python 复制代码

# 初始化各模块
cleaner = RoboticCleaner()
nav = NavigationSystem()
station = DockingStation()
yiko = VoiceControl()

# 执行清洁任务
print(cleaner.activate_deep_cleaning())
print(nav.detect_obstacle("pet_waste"))
print(station.auto_empty_dustbin())
print(yiko.process_command("Clean here please"))