Holding Strategy Using Torso to Enable Humanoid Robots to Carry Heavier Objects.

2024 IEEE/SICE International Symposium on System Integration (SII)(2024)

引用 0|浏览0
暂无评分
摘要
To alleviate the lack of workforce endemic in contemporary societies, inventory management can be delegated to robots. However, current robotic solutions cannot operate effectively in narrow spaces that have limited unoccupied pathways, such as storage rooms. Humanoid robots can work in facilities designed for humans, including narrow spaces with partially obstructed pathways, as they can overcome small obstacles on the floor by stepping over them. However, their limited torque makes it difficult for the robots to carry many of the objects typically found in storage rooms such as boxes. On the other hand, when holding an object, using multiple body parts can help to distribute the object's load. In this research, we propose a holding strategy for humanoid robots using both arms in conjunction with the torso to prevent exceeding the joint torque limit. We formulate the hands' force and the coordinates of the robot's center of gravity when holding an object with and without using the torso. Using the humanoid robot HRP-4, we compare the torque on the robot's joints when holding an object with two and three contact points. The results show that the three-point holding reduces the torque load on the shoulder and the chest joints. Moreover, we measure the torque of all joints in various torso-bending/leaning and arm-up/down postures while holding a 2-kg object using both arms and the torso. The results show that the leaning torso posture using the chest joint reduces the torque load on the shoulder and chest joints.
更多
查看译文
关键词
Humanoid Robot,Heavy Objects,Shoulder,Center Of Mass,Contact Point,Narrow Space,Inventory Management,Joint Torque,Load Torque,Storage Room,Equations Of Motion,Knee Joint,Upper Body,Variable Positions,Rotation Axis,Joint Angles,Stability Index,Blue Bars,Maximum Torque,Elbow Joint,Hand Force,Objective Weight,Robot Motion,Frontal Direction,Joint Loading,Mass Of The Object,Position Of The Robot,Part Of Joint
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要