A survey on coverage path planning for robotics

In this paper, we consider the problem of exploring an unknown environment with a team of robots. As in single-robot exploration the goal is to minimize the overall exploration time. The key problem to be solved in the context of multiple robots is to choose appropriate target points for the individual robots so that they simultaneously explore different regions of the environment. We present an approach for the coordination of multiple robots, which simultaneously takes into account the cost of reaching a target point and its utility. Whenever a target point is assigned to a specific robot, the utility of the unexplored area visible from this target position is reduced. In this way, different target locations are assigned to the individual robots. We furthermore describe how our algorithm can be extended to situations in which the communication range of the robots is limited. Our technique has been implemented and tested extensively in real-world experiments and simulation runs. The results demonstrate that our technique effectively distributes the robots over the environment and allows them to quickly accomplish their mission.

/pdf/coordinated-multi-robot-exploration-12skya2l4l.pdf

Coordinated multi-robot exploration

A variety of techniques are available enabling both invasive measurement, where the monitoring device is installed in the medium of interest, and noninvasive measurement where the monitoring system observes the medium of interest remotely. In this article we review the general techniques available, as well as specific instruments for particular applications. The issues of measurement criteria including accuracy, thermal disturbance and calibration are described. Based on the relative merits of different techniques, a guide for their selection is provided.

Review of temperature measurement

It is shown that the Abel inversion, onion-peeling, and filtered backprojection methods can be intercompared without assumptions about the object being deconvolved. If the projection data are taken at equally spaced radial positions, the deconvolved field is given by weighted sums of the projections divided by the data spacing. The weighting factors are independent of the data spacing. All the methods are remarkably similar and have Abelian behavior: the field at a radial location is primarily determined by the weighted differences of a few projections around the radial position. Onion-peeling and an Abel inversion using two-point interpolation are similar. When the Shepp-Logan filtered backprojection method is reduced to one dimension, it is essentially identical to an Abel inversion using three-point interpolation. The weighting factors directly determine the relative noise performance: the three-point Abel inversion is the best, while onion peeling is the worst with approximately twice the noise. Based on ease of calculation, robustness, and noise, the three-point Abel inversion is recommended.

One-dimensional tomography: a comparison of Abel, onion-peeling, and filtered backprojection methods.

https://hal.archives-ouvertes.fr/hal-01684295/document

Human-aware robot navigation: A survey

Abs t rac t Much of the focus of the research effort in path planning for mobile robots has centred on the problem of finding a path from a start location to a goal location, while minimising one or more parameters such as length of path, energy consumption or journey time. A path of complete coverage is a planned path in which a robot sweeps all areas of free space in an environment in a systematic and efficient manner. Possible applications for paths of complete coverage include autonomous vacuum cleaners, lawn mowers, security robots, land mine detectors etc. This paper will present a solution to this problem based upon an extension to the distance transform path planning methodology. The solution has been implemented on the self-contained autonomous mobile robot called the Yamabico.

/pdf/planning-paths-of-complete-coverage-of-an-unstructured-308uxz4de8.pdf

Planning Paths of Complete Coverage of an Unstructured Environment by a Mobile Robot

In this paper, we discuss the trajectory control for a wheeled inverse pendulum type mobile robot. The robot has two independent driving wheels on the same axle, and a gyro type sensor to measure the inclination angular velocity of the body and rotary encoders to measure wheel rotation. The purpose of this work is to make a robot autonomously navigate in a plane while keeping its own balance. The control algorithm consists of three parts: balance and velocity control, steering control and straight line tracking control. We designed and implemented a vehicle command system for such robot to control using the proposed algorithm. Experiments of the navigation in a real indoor environment have been performed using our experimental robot “Yamabico Kurara”.

Trajectory Tracking Control for Navigation of the Inverse Pendulum Type Self-Contained Mobile Robot

Trajectory Tracking Control for Navigation of the Inverse Pendulum Type Self-Contained Mobile Robot.

Our goal is to configure an automatic baggage-transportation system by an inverted pendulum robot and realize a navigation function in a real environment. The system consists of two cooperative subsystems: a balancing-and-traveling control subsystem and a navigation subsystem. Position errors of the inverted pendulum robot are often caused by a drift error in the gyro sensor and a change in the center of gravity by a loaded baggage when applying the linear state feedback control method for balancing and traveling. We have reduced the position errors for navigation by resetting the balance position occasionally while traveling with simple methods without an external observer or alternative sensors. In this paper, we state the method and show the experimental results of navigation in a real environment by the implemented robot system.

Baggage Transportation and Navigation by a Wheeled Inverted Pendulum Mobile Robot

Conventional wall following with an ultrasonic sensor uses only range data to the nearest reflecting point. However, the bearing angle information to the wall is more useful for a wall following motion. In this paper, we propose a simple wall following algorithm, where the robot moves perpendicular to the direction to the nearest reflecting point. Also, in conventional ultrasonic pulse-echo sensing, an accurate target bearing measurement is often regarded as difficult due to the wide directivity of ultrasonic transducers. However, by assuming that the ultrasonic echo returns from a single direction, the bearing angle can be measured. A new sensing method is also proposed to determine accurately the bearing angle to the reflecting point by a single ultrasonic transducer. This paper also presents experimental results from mobile robot wall following experiments using only bearing information measured by a single ultrasonic transducer. These experiments illustrate the effectiveness of proposed method.

Shin'ichi Yuta

Papers

Planning Paths of Complete Coverage of an Unstructured Environment by a Mobile Robot

Trajectory Tracking Control for Navigation of the Inverse Pendulum Type Self-Contained Mobile Robot

Trajectory Tracking Control for Navigation of the Inverse Pendulum Type Self-Contained Mobile Robot.

Baggage Transportation and Navigation by a Wheeled Inverted Pendulum Mobile Robot

Wall following using angle information measured by a single ultrasonic transducer