start_data_recording
Initiate data collection from industrial robots to monitor robot state, joint positions, TCP coordinates, and error information for analysis and diagnostics.
Instructions
开始记录机器人数据
参数:
- robot_id: 机器人ID
- record_types: 记录类型列表，可选值包括"robot_state", "joint_data", "tcp_data", "error_data"
- duration: 记录持续时间（秒），0表示持续记录直到停止
返回:
- 记录会话IDInput Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| robot_id | Yes | ||
| record_types | Yes | ||
| duration | No |
Implementation Reference
- The MCP tool handler for 'start_data_recording'. It maps string record types to DataRecordType enums and calls advanced_data_recorder.start_recording() to begin recording robot data. The @mcp.tool() decorator handles registration and schema from function signature and docstring.
def start_data_recording(robot_id: str, record_types: list, duration: float = 0): """ 开始记录机器人数据 参数: - robot_id: 机器人ID - record_types: 记录类型列表，可选值包括"robot_state", "joint_data", "tcp_data", "error_data" - duration: 记录持续时间（秒），0表示持续记录直到停止 返回: - 记录会话ID """ try: if advanced_data_recorder is None: return return_msg("高级数据记录器未初始化") # 映射记录类型字符串到枚举值 type_map = { "robot_state": DataRecordType.ROBOT_STATE, "joint_data": DataRecordType.JOINT_DATA, "tcp_data": DataRecordType.TCP_DATA, "error_data": DataRecordType.ERROR } record_enum_types = [] for record_type in record_types: if record_type in type_map: record_enum_types.append(type_map[record_type]) else: return return_msg(f"不支持的记录类型: {record_type}") # 启动记录 session_id = advanced_data_recorder.start_recording( robot_id=robot_id, record_types=record_enum_types, duration=duration ) return return_msg({"session_id": session_id, "message": "数据记录已启动"}) except Exception as e: logger.error(f"开始数据记录失败: {str(e)}") return return_msg(f"开始数据记录失败: {str(e)}")