Robot Navigation Based on Discrimination of Artificial Fields: Application to Robot Formations

In the preceding paper, a method for mobile robot navigation control based on discrimination of multiple artificial fields was introduced. In this second paper, the method is extended to robot formations. Experimental demonstrations are presented taking examples of four types of formations. The experiments cover formation initialization, maneuvering, obstacle avoidance and formation switching.     

Navigation Using an Environmental Magnetic Field for Outdoor Autonomous Mobile Robots

GPS and laser range finders are generally utilized in current robot navigation. However, information from the magnetic field and electronic compass is not, since it is dynamically changing at every position. In this paper, the relationship between the intensity of a magnetic field in the environment and its position is taken into account by utilizing a three-axis magnetic sensor to scan the magnetic field in the environment to build a database. The mobile robot navigates by performing trajectory tracking based on the database. The experimental results show that by applying the proposed method, the mobile robot is able to navigate in an outdoor environment with reliable accuracy.     

Investigations on the Hybrid Tracking Control of an Underactuated Autonomous Underwater Robot

The problem of trajectory tracking control of an underactuated autonomous underwater robot (AUR) in a three-dimensional (3-D) space is investigated in this paper. The control of an underactuated robot is different from fully actuated robots in many aspects. In particular, these robot systems do not satisfy Brockett's necessary condition for feedback stabilization and no continuous time-invariant state feedback control law exists that makes a specified equilibrium of the closed-loop system asymptotically stable. The uncertainty of hydrodynamic parameters, along with the coupled, nonlinear dynamics of the underwater robot, also makes the navigation and tracking control a difficult task. The proposed hybrid control law is developed by combining sliding mode control (SMC) and classical proportional–integral–derivative (PID) control methods to reduce the tracking errors arising out of disturbances, as well as variations in vehicle parameters like buoyancy. Here, a trajectory planner computes the body-fixed linear and angular velocities, as well as vehicle orientations corresponding to a given 3-D inertial trajectory, which yields a feasible 6-d.o.f. trajectory. This trajectory is used to compute the control signals for the three available controllable inputs by the hybrid controller. A supervisory controller is used to switch between the SMC and PID control as per a predefined switching law. The switching function parameters are optimized using Taguchi design techniques. The effectiveness and performance of the proposed controller is investigated by comparing numerically with classical SMC and traditional linear control systems in the presence of disturbances. Numerical simulations using the full set of nonlinear equations of motion show that the controller does quite well in dealing with the plant nonlinearity and parameter uncertainties for trajectory tracking. The proposed controller response shows less tracking error without the usually present control chattering. Some practical features of this control law are also discussed.     

Robot Navigation Based on Discrimination of Artificial Fields: Application to Single Robots

The paper introduces a method for local navigation of mobile robots based on the discrimination of multiple artificial fields, which correspond to targets, obstacles, robots and, if this is the case, robot collectives. Instead of just adding up all potentials, the robot discerns the pertinent potentials at its location and applies a set of motion decisions at each moment. Satisfactory results are obtained. This is the first paper of a more extensive work dealing with individual robots, unorganized groups of robot and robot formations. Here, the method is introduced, with examples for a single robot and for several independent robots.     

Mobile Robot Control Architecture for Reflexive Avoidance of Moving Obstacles

In this paper, a three-layer (deliberative, sequencing, reflexive) architecture is adopted and the structure of the reflexive layer is discussed. The objective of this architecture is to extract the basic actions that require hard-real-time execution from non-real-time-allowed behaviors by separating them into the reflexive and sequencing layers, respectively. The reflexive layer consists of resources, actions, an action coordinator and a motion controller. To guarantee the hard-real-time execution, a set of simple actions and an action coordinator are designed using the functions provided in the RTAI (Real-Time Application Interface for Linux) environment. Also, an obstacle avoidance algorithm based upon data from a laser range scanner is developed. For the purpose of avoiding a moving obstacle, which is treated as a moving circle through segmentation and circularization processes, a Kalman filter is developed to estimate the distance and the heading of the center of the moving circle. The effectiveness and real-time characteristics of the proposed reflexive layer and the developed algorithms are examined through experiments using scattered stand-still obstacles as well as a moving human.     

一处室内轮式自主移动机器人的导航控制研究

介绍了一种室内移动机器人CASIA-I.对该机器人的运动机构做了较为详细地阐述,针对该运动机构给出了机器人的运动方程和一种导航控制算法,并根据该算法进行了软件仿真和实物实验.在软件仿真和实物实验两种环境下,机器人都能够实时避开障碍物奔向目标.仿真和实验表明:该移动平台具有良好的可靠性,且该导航控制算法是一种有效的导航算法.     

轮式移动机器人组合导航方法及试验研究

该文提出了以惯性导航为基础,磁感应器修正的移动机器人组合导航方法。该方法以陀螺仪、磁感应器和里程计作为导航信息的检测器件,每隔一定的距离,利用磁感应器检测到的信息对陀螺仪和里程计进行修正,使得移动机器人能够精确定位、长时间稳定运行。一方面,消除了纯惯性导航随时间增长累积的误差;另一方面,对外界环境有较强的抗干扰能力。试验结果验证了该组合导航方法是有效、可行的,适于在线实时应用,能融合其它导航传感器信息,具有较强可扩展性。     

Multiobjective Navigation of a Guide Mobile Robot for the Visually Impaired Based on Intention Inference of Obstacles

Different from ordinary mobile robots used in a well-structured industrial workspace, a guide mobile robot for the visually impaired should be designed in consideration of multiple moving obstacles of various types and with different speeds while it adaptively maintains a certain distance from the user. Here, the moving obstacles mostly refer to pedestrians in intentional motions. Thus, navigation of the guide robot can be facilitated if the intention of each obstacle detected can be known in advance.In the paper, we propose to use a fuzzy grid-type local map in order to infer the intention of a moving obstacle. And, then, we determine the motion control of the robot by adopting a multiobjective decision making method in order to take into consideration various requirements including goal-seeking, multiple obstacle avoidance and maintenance of a certain distance from the user. To show the effectiveness of the proposed method, some experimental results are provided.