Many kinds of peg-in-hole assembly strategies for an industrial robot have been reported in recent years. Most of these strategies are realized by utilizing visual and force sensors to assist robots. However, complex control algorithms that are based on visual and force sensors will reduce the assembly efficiency of a robot. This issue is thoughtless in traditional assembly strategies but is critical to further improve the efficiency of assembly automation. In this work, a new assembly strategy that is based on a displacement sensor and a variable compliant center is proposed to improve robot performance in assembly tasks. First, an elastic displacement device for this assembly strategy is designed, and its performance is analyzed. The displacement signal generated by the displacement sensor is used to detect the contact state of the peg and hole and to guide the robot to adjust the posture. Second, an assembly strategy, including the advantages of passive compliance and active compliance, and a simple assembly control system are designed to improve the assembly efficiency. Last, the effectiveness of the proposed assembly method is experimentally verified using a robot with 6 degrees of freedom and a chamferless peg and hole with a small clearance (0.1 mm). The experimental results show that the assembly strategy can successfully complete the precision peg-in-hole assembly and assist the robot in accurate assembly in industrial applications.
Changes in human attitudes and societal values significantly influence forest management objectives and approaches. There are important signs indicating the emergence of a new social contract for forestry on Crown lands in Canada. From the perspective of forest companies, it is imperative to manage forests for multiple purposes under a tiered and nested relationship with various stakeholders. Resource professionals, including foresters, face several challenges in their effort to facilitate innovative institutional reforms and manage forests across scales.
With the merits of superior performance and easy implementation, the harmony search (HS), a famous population-based evolutionary method, has been widely adopted to resolve global optimization problems in practice. However, the standard HS method still suffers from the defects of premature convergence and local stagnation in the complex multireservoir operation problem. Thus, this study develops an enhanced harmony search (EHS) method to improve the HS’s search ability and convergence rate, where adaptive parameter adjustment strategy is used to enhance the global search performance of the swarm, while the elite-learning evolutionary mode is used to improve the converge trajectory of the population. To verify its practicability, EHS is applied to solve numerical optimization and multireservoir operation problems. The results show that EHS can produce better results than several existing methods in different cases. For instance, the mean objective of EHS is improved by about 23.9%, 28.7% and 26.8% compared with particle swarm optimization, differential evolution and gravitational search algorithm in 1998–1999 typical runoff case. Hence, an effective optimizer is developed for sustainable ecological operation of cascade hydropower reservoirs in river ecosystem.
This paper studies four patterns for the maneuverability of robotic dolphins: turning with flapping flippers, turning with swing flippers, turning with head offset, and turning with head-flipper coordination. Turning maneuverability is one of the important evaluation indexes for the performance of underwater bionic robots, and existing literature has rarely theoretically or experimentally evaluated turning maneuverability for the latter two turning patterns. In this paper, we establish a dynamic model for the high maneuverability of underwater bionic robots and discuss the influence of motion design parameters, including the frequency of the pectoral fins and the offset angle of the head, on the turning maneuverability, focusing on the turning angular velocity and turning radius. To verify the effectiveness and control accuracy of the dynamic model, we develop a multidegree-of-freedom (multi-DOF) and high-maneuverability bionic robotic dolphin and test its maneuverability through experiments. Extensive experimental results demonstrate that the established dynamic model can successfully predict the turning maneuverability of robotic dolphins. In addition, the turning methods in this paper have better turning performance than some robotic fish. This paper provides a reference for the establishment of a maneuvering dynamics model for underwater bionic robots and a theoretical basis for the design of a turning maneuver control system. INDEX TERMSRobotic dolphin, dynamic model, turning pattern, maneuverability.
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