Relevant Region sampling strategy with adaptive heuristic for asymptotically optimal path planning

Sampling-based planning algorithm is a powerful tool for solving planning problems in highdimensional state spaces.In this article,we present a novel approach to sampling in the most promising regions,which significantly reduces planning time-consumption.The RRT#algorithm defines the Relevant Region based on the cost-to-come provided by the optimal forward-searching tree.However,it uses the cumulative cost of a direct connection between the current state and the goal state as the cost-to-go.To improve the path planning efficiency,we propose a batch sampling method that samples in a refined Relevant Region with a direct sampling strategy,which is defined according to the optimal cost-to-come and the adaptive cost-to-go,taking advantage of various sources of heuristic information.The proposed sampling approach allows the algorithm to build the search tree in the direction of the most promising area,resulting in a superior initial solution quality and reducing the overall computation time compared to related work.To validate the effectiveness of our method,we conducted several simulations in both SE(2)and SE(3)state spaces.And the simulation results demonstrate the superiorities of proposed algorithm.

Optimal Design for Anti-Skid Control of Electric Vehicles by Fuzzy Approach

In this paper,a new fuzzy approach is applied to optimal design of the anti-skid control for electric vehicles.The anti-skid control is used to maintain the wheel speed when there are uncertainties.The control is able to provide an appropriate torque for wheels when the vehicle is about to skid.The friction coefficient and the moments of inertia of wheels and motor are considered as uncertain parameters.These nonlinear,bounded and time-varying uncertainties are described by fuzzy set theory.The control is deterministic and is not based on IF-THEN fuzzy rules.Then,the optimal design for this fuzzy system and control cost is proposed by fuzzy information.In this way,the uniform boundedness and uniform ultimate boundedness are guaranteed and the average fuzzy performance is minimized.Numerical simulations show that the control can prevent vehicle skidding with the minimum control cost under uncertainties.

An Automated Negotiation Protocol Based On Game Theory

With the goal of meeting one-to-many negotiation mechanism in the process of inter-basin water transfer, according to features of all interest subjects in analysis of inter-basin water transfer, a one-to-many synchronous bidding negotiation model based on bidding rules of game theory is structured, which analyzes and negotiates the functions, code of conduct and information expression of each subject. In order to optimize overall interests and individual interests, and a series of parameters in the negotiation, the paper propose various rules corresponding to the negotiation model so that the efficiency of each interest subject and fair distribution of negotiation proceeds can be safeguarded in the inter-basin water transfer system.

Erratum to "A survey of the development of biomimetic intelligence and robotics" [Biomim. Intell. Robotics 1 (2021) 100001]

The publisher regrets that the Declaration of Competing Interest statements was not included in the published version of the article "A survey of the development of biomimetic intelligence and robotics".The appropriate Declaration of Competing Interest statement,provided by the authors,is included below.

A survey of the development of biomimetic intelligence and robotics

Biomimetics is the development of novel theories and technologies by emulating the models and systems of nature.The transfer of function from biological science into engineering promotes emerging research areas across many disparate disciplines.Recently,advances in biomimetic intelligence and robotics have gained great popularity.Biomimetic robotics are designed with biological characteristics and functions to be applied in different scenarios,such as humanoid robot in the home environment,quadruped robot in the field,and bird-like flying robot in the sky.Biomimetic intelligence aims to solve many complex problems by studying the principles of biological systems,resulting in a series of efficient algorithms,such as the genetic algorithm and neural network.Biomimetic intelligence further facilitates the performance of biomimetic robotics,making it possible to be deployed in more and more practical applications.This survey introduces the development of biomimetic intelligence and biomimetic robotics.We survey different biomimetic robots,biomimetic sensors and sensing technologies,and popular biomimetic intelligence algorithms.The conclusion is drawn by discussing current challenges and future research directions.