๐ค AI Summary
ๆฌๆๆๅบไบไธ็งๅบไบๅบๅ่ฝๅๅธไผๅ็็ณป็ป็บง่ฝป้ๅๆนๆณ๏ผ้่ฟๅๅๅ้
ๅไฝ่ดจ้ๅบๅ่ฝๅนถ็ปๅๅค็งไผๅๆๆฏ๏ผๅฎ็ฐๆๅกๆบๅจไบบ็่ฝป้ๅ่ฎพ่ฎกไธๆง่ฝๆๅใ
๐ Abstract
Service robots work with people and are highly expected to be lightweight for safety, agility and energy conservation. As a complex mechanical system, a robot consists of a large number of components and has various working configurations and load environments. An effective method for achieving system-level optimal robot design is a crucial requirement, but it poses significant challenges. In this study, we introduce a novel approach to optimize the distribution of strain energy, which can significantly improve the effectiveness of systematic optimization in a complex system. First, we present and demonstrate that the strain energy per unit mass should be uniformly distributed in an optimal lightweight mechanical system. Based on this criterion, the system-level problem can be decoupled and the design objective of each part can be assigned based on the strain energy. Then, each part can be optimally designed separately according to its specific circumstances by using different approaches, such as size optimization, topological optimization, and material optimization. In this way, the optimization is at the system level, while the computational complexity is at the part level. Weight reduction and improvements in mechanical properties can be obtained simultaneously. As an example, this method is applied to an arbitrarily designed robotic arm, and its effectiveness is further demonstrated in the cases of lightweight with stiffness improvement, considering multiple materials, multiple working conditions, and vibration performance.