首页|Research from Arizona State University Yields New Findings on Robotics (Design of a wearable shoulder exoskeleton robot with dual-purpose gravity compensation and a compliant misalignment compensation mechanism)
Research from Arizona State University Yields New Findings on Robotics (Design of a wearable shoulder exoskeleton robot with dual-purpose gravity compensation and a compliant misalignment compensation mechanism)
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NETL
NSTL
Cambridge Univ Press
Investigators publish new report on robotics. According to news originating from Tempe, Arizona, by NewsRx correspondents, research stated, "This paper presents the design and validation of a wearable shoulder exoskeleton robot intended to serve as a platform for assistive controllers that can mitigate the risk of musculoskeletal disorders seen in workers." Financial supporters for this research include Division of Civil, Mechanical And Manufacturing Innova- tion. Our news journalists obtained a quote from the research from Arizona State University: "The design features a four-bar mechanism that moves the exoskeleton's center of mass from the upper shoulders to the user's torso, dual-purpose gravity compensation mechanism located inside the four-bar's linkages that supports the full gravitational loading from the exoskeleton with partial user's arm weight compensation, and a novel 6 degree-of-freedom (DoF) compliant misalignment compensation mechanism located between the end effector and the user's arm to allow shoulder translation while maintaining control of the arm's direction. Simulations show the four-bar design lowers the center of mass by $ 11 $ cm and the kinematic chain can follow the motion of common upper arm trajectories. Experimental tests show the gravity com- pensation mechanism compensates gravitational loading within $ \pm 0.5 $ Nm over the range of shoulder motion and the misalignment compensation mechanism has the desired 6 DoF stiffness characteristics and range of motion to adjust for shoulder center translation."
Arizona State UniversityTempeArizonaUnited StatesNorth and Central AmericaEmerging TechnologiesMachine LearningRobotRobotics
NETL
NSTL
Cambridge Univ Press
