首页|New Findings from Nanyang Technological University Describe Advances in Robotics (Low-Cost Cable-Driven Robot Arm with Low- Inertia Movement and Long-Term Cable Durability)

New Findings from Nanyang Technological University Describe Advances in Robotics (Low-Cost Cable-Driven Robot Arm with Low- Inertia Movement and Long-Term Cable Durability)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on robotics is the subjec t of a new report. According to news reporting out of Singapore, Singapore, by N ewsRx editors, research stated, “Our study presents a novel design for a cable-d riven robotic arm, emphasizing low cost, low inertia movement, and long-term cab le durability.” Financial supporters for this research include Agency For Science, Technology An d Research; Schaeffler Hub For Advanced Research At Ntu. The news editors obtained a quote from the research from Nanyang Technological U niversity: “The robotic arm shares similar specifications with the UR5 robotic a rm, featuring a total of six degrees of freedom (DOF) distributed in a 1:1:1:3 r atio at the arm base, shoulder, elbow, and wrist, respectively. The three DOF at the wrist joints are driven by a cable system, with heavy motors relocated from the end-effector to the shoulder base. This repositioning results in a lighter cable-actuated wrist (weighing 0.8 kg), which enhances safety during human inter action and reduces the torque requirements for the elbow and shoulder motors. Co nsequently, the overall cost and weight of the robotic arm are reduced, achievin g a payload-to-body weight ratio of 5:8.4 kg. To ensure good positional repeatab ility, the shoulder and elbow joints, which influence longer moment arms, are de signed with a direct-drive structure. To evaluate the design’s performance, test s were conducted on loading capability, cable durability, position repeatability , and manipulation.”

Nanyang Technological UniversitySingap oreSingaporeAsiaEmerging TechnologiesMachine LearningRobotRoboticsRobots

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Sep.18)