为了解决移动机器人在复杂环境中物体抓取规划成功率低以及规划时间长等问题,本文提出了一种基于环境信息的预处理生成移动机器人停靠位置优化算法。首先对机械臂的工作空间进行分析,得到抓取难易评价标准,将环境中目标物、障碍物以及...为了解决移动机器人在复杂环境中物体抓取规划成功率低以及规划时间长等问题,本文提出了一种基于环境信息的预处理生成移动机器人停靠位置优化算法。首先对机械臂的工作空间进行分析,得到抓取难易评价标准,将环境中目标物、障碍物以及移动底盘位置简化为点,投影到xy平面上,根据抓取难易评价标准求出移动机器人优化后的底盘停靠位置;然后针对机械臂避障问题,采用快速扩展随机树(Rapidly-exploring Random Trees,RRT)算法实现了机械臂末端及连杆与障碍物的避障;最后通过仿真和动作捕捉系统下的实验发现,采用移动机器人停靠位置优化算法可显著提高抓取规划成功率和规划速度。展开更多
Manufacturing robotics is moving towards human-robot collaboration with light duty robots being used side by side with workers. Similarly, exoskeletons that are both passive(spring and counterbalance forces) and activ...Manufacturing robotics is moving towards human-robot collaboration with light duty robots being used side by side with workers. Similarly, exoskeletons that are both passive(spring and counterbalance forces) and active(motor forces) are worn by humans and used to move body parts. Exoskeletons are also called ‘wearable robots' when they are actively controlled using a computer and integrated sensing. Safety standards now allow, through risk assessment, both manufacturing and wearable robots to be used. However, performance standards for both systems are still lacking. Ongoing research to develop standard test methods to assess the performance of manufacturing robots and emergency response robots can inspire similar test methods for exoskeletons. This paper describes recent research on performance standards for manufacturing robots as well as search and rescue robots. It also discusses how the performance of wearable robots could benefit from using the same test methods.展开更多
文摘为了解决移动机器人在复杂环境中物体抓取规划成功率低以及规划时间长等问题,本文提出了一种基于环境信息的预处理生成移动机器人停靠位置优化算法。首先对机械臂的工作空间进行分析,得到抓取难易评价标准,将环境中目标物、障碍物以及移动底盘位置简化为点,投影到xy平面上,根据抓取难易评价标准求出移动机器人优化后的底盘停靠位置;然后针对机械臂避障问题,采用快速扩展随机树(Rapidly-exploring Random Trees,RRT)算法实现了机械臂末端及连杆与障碍物的避障;最后通过仿真和动作捕捉系统下的实验发现,采用移动机器人停靠位置优化算法可显著提高抓取规划成功率和规划速度。
文摘Manufacturing robotics is moving towards human-robot collaboration with light duty robots being used side by side with workers. Similarly, exoskeletons that are both passive(spring and counterbalance forces) and active(motor forces) are worn by humans and used to move body parts. Exoskeletons are also called ‘wearable robots' when they are actively controlled using a computer and integrated sensing. Safety standards now allow, through risk assessment, both manufacturing and wearable robots to be used. However, performance standards for both systems are still lacking. Ongoing research to develop standard test methods to assess the performance of manufacturing robots and emergency response robots can inspire similar test methods for exoskeletons. This paper describes recent research on performance standards for manufacturing robots as well as search and rescue robots. It also discusses how the performance of wearable robots could benefit from using the same test methods.
