首页|Studies from University of Michigan-Dearborn Update Current Data on Robotics (Au tomatic Optimal Robotic Base Placement for Collaborative Industrial Robotic Car Painting)
Studies from University of Michigan-Dearborn Update Current Data on Robotics (Au tomatic Optimal Robotic Base Placement for Collaborative Industrial Robotic Car Painting)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on robotics have been pr esented. According to news originating from Dearborn, Michigan, by NewsRx editor s, the research stated, “This paper investigates the problem of optimal base pla cement in collaborative robotic car painting.” Financial supporters for this research include Ford Motor Company. Our news editors obtained a quote from the research from University of Michigan- Dearborn: “The objective of this problem is to find the optimal fixed base posit ions of a collection of given articulated robotic arms on the factory floor/ceil ing such that the possibility of vehicle paint coverage is maximized while the p ossibility of robot collision avoidance is minimized. Leveraging the inherent tw o-dimensional geometric features of robotic car painting, we construct two types of cost functions that formally capture the notions of paint coverage maximizat ion and collision avoidance minimization. Using these cost functions, we formula te a multi-objective optimization problem, which can be readily solved using any standard multi-objective optimizer. Our resulting optimal base placement algori thm decouples base placement from motion/trajectory planning. In particular, our computationally efficient algorithm does not require any information from motio n/trajectory planners a priori or during base placement computations.”
University of Michigan-DearbornDearbor nMichiganUnited StatesNorth and Central AmericaEmerging TechnologiesMa chine LearningRoboticsRobots
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