Software errors significantly impact software quality, and improvement of fault localization can reduce the expense of debugging. SBFL is promising approach and have received a lot of attention due to its simplicity a...
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Localization is one the key technologies of wireless sensor networks, and the problem of localization is always formulate as an optimization problem. Particle swarm optimization (PSO) is easy to implement and requires...
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Trajectory tracking for manipulators, especially when faced with complex trajectories, remains a formidable challenge in robotics. This paper introduces an approach to address this challenge with the framework we prop...
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Records technology automation is becoming increasingly essential for groups that want to make sense of immense and complicated datasets quickly and effectively. Leveraging AI-pushed structures gives a feasible solutio...
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Three tier enterprise applications introduce multiple challenges for software engineers. Although we can divide the application into three tiers, we still need to design properly each tier internally to achieve multip...
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This paper proposes an optimization method on energy consumption for public buildings based on the data-driven heuristic dynamic programming algorithm. To this end, a large amount of building data is first collected f...
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This paper presents an optimal control scheme based on model-based predictive control (MPC) for a wheeled mobile robot (WMR) with nonholonomic constraints. It is shown that, by using MPC, some advantages can be obtain...
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Inverse kinematics is a fundamental challenge for articulated robots: fast and accurate algorithms are needed for translating task-related workspace constraints and goals into feasible joint configurations. In general...
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ISBN:
(纸本)9781728173955
Inverse kinematics is a fundamental challenge for articulated robots: fast and accurate algorithms are needed for translating task-related workspace constraints and goals into feasible joint configurations. In general, inverse kinematics for serial kinematic chains is a difficult nonlinear problem, for which closed form solutions cannot easily be obtained. Therefore, computationally efficient numerical methods that can be adapted to a general class of manipulators are of great importance. In this paper, we use convex optimization techniques to solve the inverse kinematics problem with joint limit constraints for highly redundant serial kinematic chains with spherical joints in two and three dimensions. This is accomplished through a novel formulation of inverse kinematics as a nearest point problem, and with a fast sum of squares solver that exploits the sparsity of kinematic constraints for serial manipulators. Our method has the advantages of post-hoc certification of global optimality and a runtime that scales polynomially with the number of degrees of freedom. Additionally, we prove that our convex relaxation leads to a globally optimal solution when certain conditions are met, and demonstrate empirically that these conditions are common and represent many practical instances. Finally, we provide an open source implementation of our algorithm.
This paper is about a theoretic model for resource based communication using the example of an autonomous warehouse. Autonomous automata handle boxes in the warehouse just based on the information they can read in the...
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The dynamic equations of a micro-positioning Scott-Russell (SR) mechanism associated with two flexible hinges and an offset are developed to calculate the output responses. Both rigid and flexible hinges are considere...
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