Bio-inspired Design and Inverse Kinematics Solution of an Omnidirectional Humanoid Robotic Arm with Geometric and Load Capacity Constraints

Inspired by the driving muscles of the human arm,a 4-Degree of Freedom(DOF)concentrated driving humanoid robotic arm is proposed based on a spatial double parallel four-bar mechanism.The four-bar mechanism design reduces the inertia of the elbow-driving unit and the torque by 76.65%and 57.81%,respectively.Mimicking the human pose regulation strategy that the human arm picks up a heavy object by adjusting its posture naturally without complicated control,the robotic arm features an integrated position-level closed-form inverse solution method considering both geometric and load capacity limitations.This method consists of a geometric constraint model incorporating the arm angle(φ)and the Global Configuration(GC)to avoid joint limits and singularities,and a load capacity model to constrain the feasible domain of the arm angle.Further,trajectory tracking simulations and experiments are conducted to validate the feasibility of the proposed inverse solution method.The simulated maximum output torque,maximum output power and total energy consumption of the robotic arm are reduced by up to 2.0%,13.3%,and 33.3%,respectively.The experimental results demonstrate that the robotic arm can bear heavy loads in a human-like posture,effectively reducing the maximum output torque and energy consumption of the robotic arm by 1.83%and 5.03%,respectively,while avoiding joints beyond geometric and load capacity limitations.The proposed design provides a high payload–weight ratio and an efficient pose control solution for robotic arms,which can potentially broaden the application spectrum of humanoid robots.

Study on the Problem of Multistage Vaccine Production and Allocation with Capacity Constraints

Vaccination is the best way to build an immune barrier to control a new infectious disease.Considering the limited production capacity at the initial stage of vaccine production,the problem of multistage vaccine production and allocation is studied under the policy of free treatment for infected patients by the government.Given the population and infection rates of different regions and the vaccine production capacity of each stage,an integer programming model is established to minimize the sum of production-and-vaccination cost and treatment cost of infected patients,which is solved by the GUROBI solver.The correctness of the model is verified by simulation,and the necessity of considering the treatment cost of infected patients in the objective function is further analyzed,which confirmed the correctness of the free treatment policy for patients in China.A heuristic algorithm is designed to solve the large-scale problem and numerical experiments are conducted to verify the efficiency of this algorithm.Furthermore,based on the sensitivity analysis results of parameters,the optimal vaccine production and allocation strategy are proposed,which provide the decision basis for the government departments to make reasonable vaccine production and vaccination plan.

A weighted network evolving model with capacity constraints

Most of existing works on complex network assumed that the nodes and edges were uncapacitated during the evolving process,and displayed "rich club" phenomenon.Here we will show that the "rich club" could be changed to "common rich" if we consider the node capacity.In this paper,we define the node and edge attractive index with node capacity,and propose a new evolving model on the base of BBV model,with evolving simulations of the networks.In the new model,an entering node is linked with an existing node according to the preferential attachment mechanism defined with the attractive index of the existing node.We give the theoretical approximation and simulation solutions.If node capacity is finite,the rich node may not be richer further when the node strength approaches or gets to the node capacity.This is confirmed by analyzing the passenger traffic and routes of Chinese main airports.Due to node strength being function of time t,we can use the theoretical approximation solution to forecast how node strength changes and the time when node strength reaches its maximum value.

Hybrid algorithm for project scheduling with capacity constraint

Motivated by the projects constrained by space capacity and resource transporting time, a project scheduling probIem with capacity constraint was modeled. A hybrid algorithm is proposed, which uses the ideas of bi-level scheduling and project decomposition technology, and the genetic algorithm and tabu search is combined. Topological reordering technology is used to improve the efficiency of evaluation. Simulation results show the proposed algorithm can obtain satisfied scheduling results in acceptable time.

Production Decision Based on Discounted Price and Delivery Frequency for Garment Original Equipment Manufacturer with Constrained Capacity

Original equipment manufacturers(OEM) have never been so important and powerful as it is today in garment manufacturing industry.The OEMsupplier's production decisions always have a great impact on the market performance and the profits of a garment brand manufacturer.With constrained capacity and multiply buyers,howto make reasonable production decisions is an urgent problem for OEMsuppliers.A price discount model with a single OEMsupplier and two buyers is proposed to deal with the problem.Based on this model,the OEMsupplier could satisfy buyers' demands and guarantee their profits as well through adjusting price and delivery frequency.A numerical example validates the validity of the model.

A RISK-AVERSE NEWSVENDOR MODEL WITH LIMITED CAPACITY AND OUTSOURCING UNDER THE CVAR CRITERION

For seasonal products, the retailers usually launch various marketing ettorts, llKe aaverusmg tmu promotion, to promote them in a selling season. While facing large demand from the customers, one should take the capacity constraint and outsotlrcing into consideration. Considering the shorten life cycles of most products, in this paper we adopt the traditional newsvendor model to investigate the optimal marketing effort along with optimal order quantity. We address the risk aversion issue and characterize the influence of the sellers＇ risk propensity with CVaR criterion, and we develop an effective algorithm to obtain the optimal strategy. The impact of sellers＇ risk propensity on the performance of the system is illustrated via numerical examples, The innovation of this paper is threefold. First, the optimal joint strategy of the marketing effort and order quantity is investigated and an efficient algorithm to find the optimal strategy is developed. Second, the capacity constraint option and an outsourcing strategy are studied jointly for excess products. Finally, the risk propensity of the seller and its influence are investigated by using the CVaR criterion, through which we obtain some new managerial insights.

OPTIMAL PRICING, PRODUCTION, AND SALES POLICIES FOR NEW PRODUCT UNDER SUPPLY CONSTRAINT

This paper considers a firm that sells a durable product with a given market potential.The purpose of the firm is to maximize its profit by determining how much capacity to install before the sales horizon, how many products to produce in accordance with the capacity, and how many products to sell by pricing. Appealing to Pontryagin maximum principle in control theory, the authors obtain the closed-forms of all optimal decisions the firm should make. Furthermore, the optimal production rate and optimal sales rate are both equal to the demand rate, which is caused by the optimal pricing policy during the whole horizon, and the optimal pricing path is increasing with the cost of installing a unit of capacity. Furthermore, numerical analysis reveals the visual impression of the relationship of the parameters.