Nak Yong Ko

The lane-curvature method for local obstacle avoidance

The lane-curvature method (LCM) presented in this paper is a new local obstacle avoidance method for indoor mobile robots. The method combines curvature-velocity method (CVM) with a new directional method called the lane method. The lane method divides the environment into lanes, and then chooses the best lane to follow to optimize travel along a desired heading. A local heading is then calculated for entering and following the best lane, and CVM uses this heading to determine the optimal translational and rotational velocities, considering the heading direction, physical limitations, and environmental constraints. By combining both the directional and velocity space methods, LCM yields safe collision-free motion as well as smooth motion taking the dynamics of the robot into account.

Avoidability measure in moving obstacle avoidance problem and its use for robot motion planning

This paper presents a new solution approach to moving obstacle avoidance problem of a robot. A new concept avoidability measure (AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function (VDF) is derived as a function of the distance from the obstacle to the robot and outward speed of the obstacle relative to the robot. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terms of the VDF, an artificial potential field is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived from the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid moving obstacles in real time. Since the algorithm considers the mobility of the obstacle as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

Real-time EtherCAT Master Implementation on Xenomai for a Robot System

This paper describes a real-time EtherCAT Master library. The library is developed using Xenomai. Xenomai is a real-time development framework. It cooperates with the Linux kernel, in order to provide a pervasive, interface-agnostic, hard real-time support to user-space applications, seamlessly integrated into the GNU/Linux environment. The proposed master library implements EtherCAT protocol for master side, and supports Application Programming Interfaces(APIs) for programming of real-time application which controls EtherCAT slave.

A lane based obstacle avoidance method for mobile robot navigation

This paper presents a new local obstacle avoidance method for indoor mobile robots. The method uses a new directional approach called the Lane Method. The Lane Method is combined with a velocity space method i.e., the Curvature-Velocity Method to form the Lane-Curvature Method(LCM). The Lane Method divides the work area into lanes, and then chooses the best lane to follow to optimize travel along a desired goal heading. A local heading is then calculated for entering and following the best lane, and CVM uses this local heading to determine the optimal translational and rotational velocities, considering some physical limitations and environmental constraint. By combining both the directional and velocity space methods, LCM yields safe collision-free motion as well as smooth motion taking the physical limitations of the robot motion into account.

Trajectory modification using elastic force for collision avoidance of a mobile manipulator

This paper proposes a method for collision avoidance of a mobile manipulator. The method deals with the problem of driving a mobile manipulator from a starting configuration to a goal configuration avoiding obstacles. It modifies planned trajectory at every sampling time using elastic force and potential field force. It puts way poses throughout a planned trajectory, and the trajectory modification is accomplished by adjusting the way poses. The way poses are adjusted subject to the elastic force and the potential field force. The procedure repeats until the robot reaches its goal configuration through the way poses. This method results in smooth and adaptive trajectory in an environment with moving as well as stationary obstacles.

Monte Carlo Localization of Underwater Robot Using Internal and External Information

This paper proposes a method for localization of an underwater robot. The method uses Monte Carlo algorithm called the particle filter. It predicts the pose of the robot using the internal sensor information from thrusters, inertial sensors, and electronic compass. A correction procedure follows the prediction. The correction uses external sensor information, that is, the distance from landmarks whose locations are known a priori. The prediction and correction process use samples of robot pose in stochastic and probabilistic approach. Though the external information available from the sensors could include depth, angle and angle rates of yaw, pitch, and roll, the proposed method uses only the distance from some beacons. In contrast to the classical methods which usually use either trilateration principle or dead reckoning to calculate the pose, the proposed approach fuses motion and internal sensor information with the external sensor information. The simulation shows that localization is possible even if only one or two beacons are available for range measurement. The experiments which uses two beacons in a tank suggest that the proposed method can be effective where the number of beacons is limited due to geographical features of the robot work area.

Investigating voice communication over multipath wireless mobile ad hoc network

With the rapid growth and popularity of wireless LANs (WLANs), a demand of Voice over IP (VoIP) is also increasing. In recent years, dominant trend of development in Mobile Ad hoc Networks (MANET) technology makes VoIP services more appealing. However, it is still quite challenging to ensure quality voice communication in MANET. Some of these challenges include packet loss due to network congestion, and variable packet latency. Not only traditional single-path ad-hoc routing but also traditional voice codec fails to perform well under these conditions. In this paper, we depict a framework for VoIP over multipath multihop wireless network, in which we propose multipath ad-hoc routing and traffic allocation approach.

An analytic approach to moving obstacle avoidance using an artificial potential field

This paper proposes a unified method for moving obstacle avoidance of a robot. The method incorporates the artificial potential field (APF) concept into view-time based motion planning where the driving force is generated at every interval of the view-time. The view-time is defined as the time set from one sampling time instant to the next. The velocity and acceleration of the moving obstacle is assumed to be monitored or priorly known at each sampling time. At each sampling time, an accessible region that will be swept by the obstacle in the next view-time is predicted from the velocity, acceleration, and dynamic constraints of the obstacle. Then, an APF which exerts repulsive force on the robot is constructed around the accessible region. During the view-time, the force induced by the artificial potential field drives the robot away from the accessible obstacle trajectories in real-time. The dynamic constraints of the robot are also considered. Application of the described procedure at each successive sampling time from the initial to final location yields the collision-free trajectory for moving obstacle avoidance.

An approach to robot motion planning for time-varying obstacle avoidance using the view-time concept

An analytic solution approach to the time-varying obstacle avoidance problem is adopted. The problem considers the collision between any link of the robotic manipulator and the time-varying obstacle. The information on the motion and shape change of the obstacle is given prior to robot motion planning. To facilitate the problem, we analyze and formulate it mathematically in a robot joint space. We then introduce the view-time concept and analyze its properties. Using the properties of the view-time, a view-time based motion planning method is proposed. The view-time based method plans the robot motion by units of the view-time. In every view-time, it uses a stationary obstacle avoidance scheme. The proposed method is applied to the motion planning of a 2 DOF robotic manipulator in an environment with a polyhedral moving obstacle.

Comparison of Kalman filter and particle filter used for localization of an underwater vehicle

This paper compares filtering methods used for localization of an underwater robot: Kalman filter and particle filter. Kalman filter and particle filter are major filters for estimation of robot pose on the ground. They are adapted for underwater robot localization. While Kalman filter can be used for linear or linearized processes and measurement system, the particle filter can be used for nonlinear systems. Also, the uncertainty of Kalman filter is restricted to Gaussian distribution, while the particle filter can deal with non-Gaussian noise distribution. In cases where abrupt sensor noise is rarely observed, both filters work fairly well. However, when sensor noise exhibits jerky error, Kalman filter results in location estimation with hopping while particle filter still produces robust localization. The paper also compares performance of these filters under various measurement uncertainty and process uncertainty. The methods are compared and verified through experiments.