According to the features of movements of humanoid robot, a control system for humanoid robot walking on uneven terrain is present. Constraints of stepping over stairs are analyzed and the trajectories of feet are cal...According to the features of movements of humanoid robot, a control system for humanoid robot walking on uneven terrain is present. Constraints of stepping over stairs are analyzed and the trajectories of feet are calculated by intelligent computing methods. To overcome the shortcomings resulted from directly controlling the robot by neural network （NN） and fuzzy logic controller （FLC）, a revised particle swarm optimization （PSO） algorithm is proposed to train the weights of NN and rules of FLC. Simulations and experiments on different control methods are achieved for a detailed comparison. The results show that using the proposed methods can obtain better control effect.展开更多
The health of people around the world and the global economy are under substantial threat from the outbreak of pandemics[1].Controlling pandemics is extremely challenging,with preventing the spread of pathogens the mo...The health of people around the world and the global economy are under substantial threat from the outbreak of pandemics[1].Controlling pandemics is extremely challenging,with preventing the spread of pathogens the most important and critical step.Of all preventative actions,body temperature screening is undoubtedly highly necessary and effective[2].展开更多
Benefit from the high payload-to-weight ratio, parallel robots are expected to have a high potential for energy savings. However,it is a challenging issue to evaluate the energy efficiency of parallel robots with a qu...Benefit from the high payload-to-weight ratio, parallel robots are expected to have a high potential for energy savings. However,it is a challenging issue to evaluate the energy efficiency of parallel robots with a quantitative method. Quantitative energy efficiency evaluation methods include energy efficiency evaluation models and indices which mathematically describe the relationship between energy consumers in models and design variables of robots, such as geometry, mass and inertia parameters.Considering the structural features of parallel robots, the chains and the end effectors are identified as two separated energy consumers. Besides, the chains in parallel robots are identified as a transmission system which transfers energy from drives to the end effectors. On this basis, an energy efficiency evaluation model considering the change rate of kinetic energy stored in chains is built. The kinetic energy change rate of chains is influenced by design variables of robots as well as motion of the end effector.In order to give a quantitative description of energy efficiency performance of parallel robots, indices considering arbitrary velocity vector of the end effector are proposed. The evaluation method is suitable for all kinds of parallel robots with various motion conditions. Furthermore, the method can be used to optimize machining parameters and guide the design of energyefficient machines.展开更多
基金This material is based upon work funded by State Key Laboratory of Robotics and System （HIT） Foundation of China under Grant No. SKLRS-2012-MS-06, China Postdoctoral Science Foundation under Grant No. 2013M531022, Research project of laboratory work in universities of Zhejiang Province under Grant No. ZD201504, Educational technology research program of Zhejiang Province under Grant No. JA027.
文摘According to the features of movements of humanoid robot, a control system for humanoid robot walking on uneven terrain is present. Constraints of stepping over stairs are analyzed and the trajectories of feet are calculated by intelligent computing methods. To overcome the shortcomings resulted from directly controlling the robot by neural network （NN） and fuzzy logic controller （FLC）, a revised particle swarm optimization （PSO） algorithm is proposed to train the weights of NN and rules of FLC. Simulations and experiments on different control methods are achieved for a detailed comparison. The results show that using the proposed methods can obtain better control effect.
文摘The health of people around the world and the global economy are under substantial threat from the outbreak of pandemics[1].Controlling pandemics is extremely challenging,with preventing the spread of pathogens the most important and critical step.Of all preventative actions,body temperature screening is undoubtedly highly necessary and effective[2].
基金supported by the National Natural Science Foundation of China(Grant Nos.51675290 and 51425501)Beijing Municipal Science and Technology Commission(Grant No.Z181100003118003)
文摘Benefit from the high payload-to-weight ratio, parallel robots are expected to have a high potential for energy savings. However,it is a challenging issue to evaluate the energy efficiency of parallel robots with a quantitative method. Quantitative energy efficiency evaluation methods include energy efficiency evaluation models and indices which mathematically describe the relationship between energy consumers in models and design variables of robots, such as geometry, mass and inertia parameters.Considering the structural features of parallel robots, the chains and the end effectors are identified as two separated energy consumers. Besides, the chains in parallel robots are identified as a transmission system which transfers energy from drives to the end effectors. On this basis, an energy efficiency evaluation model considering the change rate of kinetic energy stored in chains is built. The kinetic energy change rate of chains is influenced by design variables of robots as well as motion of the end effector.In order to give a quantitative description of energy efficiency performance of parallel robots, indices considering arbitrary velocity vector of the end effector are proposed. The evaluation method is suitable for all kinds of parallel robots with various motion conditions. Furthermore, the method can be used to optimize machining parameters and guide the design of energyefficient machines.
