煤矿机器人环境感知与路径规划关键技术
Key technologies of coal mine robots for environment perception and path planning
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摘要: 煤炭生产是典型的高危、艰苦行业,现有煤矿设备需要技术工人直接或间接参与,存在较高 的安全隐患和成本代价。 从产业的安全性和效率性考虑,使用煤矿机器人代替人参与煤炭生产是 煤矿企业实现“少人化”甚至“无人化”生产的必然途径,也符合“数字化”矿山的基本目标。 煤矿 机器人自主运行需要环境感知技术获取工作环境信息,完成自身安全状态评估并为机器人决策规 划提供基础数据,而路径规划是实现机器人移动的基础,也是连接环境感知和底层控制的关键技 术。 综述了掘进类、采煤类、运输类、安控类、救援类等 5 类煤矿机器人的工作原理、功能需求、任务 目标和环境复杂性,分析了近 15 a 来 5 类煤矿机器人在以上环境感知与路径规划关键技术的重要 研究成果。 最后,从感知与认知、规划与决策和系统集成等 3 个方面展望了煤矿机器人关键技术的 未来发展方向及挑战。 感知与认知的发展趋势不但要求煤矿机器人具备感知能力,还需要机器人 根据少量可用信息完成规律事件外的认知学习,其关键挑战是开发多元传感器融合技术和小样本 学习方法;规划与决策的发展方向可分为单目标点规划和多目标点决策,煤矿机器人使用感知与认 知信息实现点对点的单目标路径规划及避障,并根据工作需求完成多任务之间的最优化决策,提高 煤矿机器人工作效率;研制机器人协作系统和通讯交互系统是系统集成的主要挑战,通过完备的 内、外网络系统完成煤矿企业管理人员、技术工人、机器人设备之间的实时闭环交互,形成多数量、 多工种煤矿机器人的协调合作。Abstract: Coal production is a typical highrisk and hard work. Existing coal mine equipment requires skilled workers to directly or indirectly participate,which has high security risks and costs. Considering safety and efficiency of the industry,using robots in coal production instead of workers is an inevitable way for coal mining companies to achieve “fewerpeople” or even “unmanned” production. It is also in line with the basic goal of “digital mines”. In the autonomous operation of coal mine robots,environmental perception technology,which would realize robots’ safety status assessment and provide basic data for decisionmaking and planning,is used to obtain workspace information. Moreover,path planning is the basis for robot movement and a key technology connecting environment perception and underlying control. The working principle,functional requirements,task objectives and environmental complexity of 5 types of coal mine robots(i.e. roadheader robots,shearer robots,transport robots,inspection robots and rescue robots) are summarized in this paper. We organize and analyse the important research of coal mine robots focusing on the environment perception and path planning in the past 15 years. Finally,the future development direction of key technologies of coal mine robots is prospected from 3 aspects:perception and cognition,planning and decision and system integration. The development trend of perception and cognition not only requires coal mine robots to have perception capabilities,but also requires robots to complete cognitive learning based on a small amount of available information outside of regular events. The key challenge is to develop multisensor fusion technology and fewshot learning methods. The development direction of planning and decision can be divided into singletarget planning and multitarget decisionmaking. Coal mine robots use perception and cognitive information to achieve pointtopoint path planning and obstacle avoidance,and complete multitask optimization according to work requirements. Thereby,the working efficiency of coal mine robots can be improved. The development of robot collaboration systems and communication interactive systems is the main challenge for system integration. Through a complete internal and external network system,realtime and closedloop interaction among coal mine managers,technical workers and robot equipment and cooperation between multinumber/multitype of coal mine robots will be completed.