Huaiyu Wu

Trajectory tracking control of nonholonomic mobile robots by Backstepping

This paper mainly research about the trajectory tracking control of nonholonomic mobile robots. Using the idea of Backstepping, a simple virtual variable is proposed and the corresponding feedback control law of nonholonomic mobile robot is designed via lyapunov direct method, at the same time it can be proved that the control effect can achieve global asymptotic stability. The proposing of a simple virtual variable makes the control law designing more easy. A simulation proves the systems global asymptotic stability, meanwhile, verifies the correctness and effectiveness of the control law.

Escaping from obstacle zone for mobile robot based on maximum distance priority mechanism

This paper presents an obstacle avoidance method of escaping from obstacle zone based on maximum distance priority mechanism, aiming at the obstacle avoidance with limited local environmental information instead of known global environmental information. Acquiring local environmental information by laser range finder (LRF) which collects distance data between object and mobile robot, we use a method of finding feasible directions to search feasible sections, which are divisions of LRF distance data. And a maximum distance priority mechanism is proposed to select feasible section containing maximum distance as reference motion section, enabling mobile robot always to move in the direction of escaping from obstacle zones. Meanwhile, error control is designed to optimize the method and make it more practical. An analysis experiment of laser range finder data from three representative scenes is carried out to demonstrate the principle of the proposed method. Besides, we conduct a contrast experiment in MT-R wheeled mobile robot between maximum distance priority mechanism and maximum open angle priority mechanism. In the end, maximum distance priority mechanism overcomes the problems for mobile robot, which includes endless wandering and turning around in obstacle zone. The results of experiments illustrate effectiveness of the proposed method, and reveal its well real-time performance and obstacle avoidance efficiency.

Mobile olfaction robot odor source localization based on wireless sensor network

The mobile olfaction robot is combined with the wireless sensor network to realize the odor source location. Mobile robot is a fusion of gas sensors and infrared ranging sensors etc. Environment information detected by wireless sensor network could provide general distribution of odor source for a mobile robot. Therefore, the time-consuming in traditional plume discovery could be avoided in the process of random searching. At the same time, the wireless sensor module is equipped on the mobile robots, so that the operator could obtain the information of source coordinate on the personal computer(PC) directly. The related experiment demonstrates that the method could quickly find the leakage source and locate the odor source.

State estimation of moving objects based on ellipses

State estimation of moving objects in complex environments is the foundation for robot cognition and intelligence. This study focuses on targets identification and states estimation utilizing a single laser scanner, which adopts multiple ellipses to model any possible object in the field of view of the sensor. First, a nearest neighbor clustering algorithm is used to achieve the segments of the data frame. Each segment represents a potential target that consists of a group points close to each other in Euclidean distance. Then, an ellipse can be optimized with covering the group points by minimizing the ellipse area. The solution can be obtained by solving a traditional Lowner-John ellipsoid problem. The movement of the target will be replaced by the motion of the corresponding ellipse. Next, the target states are estimated by data association technique on their frame sequences. Finally, experiments with a still or moving robot mounted with a laser sensor are taken indoor and outdoor to verify the feasibility and effectiveness of our novel method.

Receding horizon control for mobile robot path planning in unknown dynamic environments

Path planning is one of the critical issues in mobile robot applications. Traditional methods for path planning in unknown dynamic environment generally plan one step rather than multiple controlling steps. This paper proposes an approach with multiple controlling steps which integrates receding horizon control (RHC) for mobile robot path planning in which the obstacle avoidance problem is converted into mathematic constraint. Besides, the distance from target to robot is optimized through involving a quadratic cost function. Finally, a quadratic constrained quadratic programming (QCQP) is generated, from which a sequence including multiple control steps is easily obtained. Based on the proposed approach, simulations are demonstrated to verify the effectiveness of the novel method.

Study on a New Heuristic Crossover for the Traveling Salesman Problem

When the genetic algorithms were applied to practical problems, the use of heuristic genetic operators which appropriately incorporated the problem-specific knowledge could improve the performance of the algorithms. A new heuristic crossover operator for the traveling salesman problem was proposed. This crossover realized the construction of the offspring by inheriting the shortest edge which does not cause a cycle from the parents and producing the shortest edge. In this way, the length of offspring tour was usually shorter than their parents. The numerical simulations on geometric and random traveling salesman problems demonstrated that this heuristic crossover operator outperformed the order crossover operator and enhanced edge recombination crossover operator.