FRAMEWORK FOR AD HOC NETWORK COMMUNICATION IN MULTI-ROBOT SYSTEMS

Assume a team of mobile robots operating in environments where no communication infrastructure like routers or access points is available. The robots have to create a mobile ad hoc network, in that case, it provides communication on peer-to-peer basis. The paper gives an overview of existing solutions how to route messages in such ad hoc networks between robots that are not directly connected and introduces a design of a software framework for realization of such communication. Feasibility of the proposed framework is shown on the example of distributed multi-robot exploration of an a priori unknown environment. Testing of developed functionality in an exploration scenario is based on results of several experiments with various input conditions of the exploration process and various sizes of a team and is described herein

Push, Stop, and Replan: An Application of Pebble Motion on Graphs to Planning in Automated Warehouses

The pebble-motion on graphs is a subcategory of multi-agent pathfinding problems dealing with moving multiple pebble-like objects from a node to a node in a graph with a constraint that only one pebble can occupy one node at a given time. Additionally, algorithms solving this problem assume that individual pebbles (robots) cannot move at the same time and their movement is discrete. These assumptions disqualify them from being directly used in practical applications, although they have otherwise nice theoretical properties. We present modifications of the Push and Rotate algorithm [1], which relax the presumptions mentioned above and demonstrate, through a set of experiments, that the modified algorithm is applicable for planning in automated warehouses

Simple yet stable bearing-only navigation

This article describes a simple monocular navigation system for a mobile robot based on the map-and-replay technique. The presented method is robust and easy to implement and does not require sensor calibration or structured environment, and its computational complexity is independent of the environment size. The method can navigate a robot while sensing only one landmark at a time, making it more robust than other monocular approaches. The aforementioned properties of the method allow even low-cost robots to effectively act in large outdoor and indoor environments with natural landmarks only. The basic idea is to utilize a monocular vision to correct only the robot's heading, leaving distance measurements to the odometry. The heading correction itself can suppress the odometric error and prevent the overall position error from diverging. The influence of a map-based heading estimation and odometric errors on the overall position uncertainty is examined. A claim is stated that for closed polygonal trajectories, the position error of this type of navigation does not diverge. The claim is defended mathematically and experimentally. The method has been experimentally tested in a set of indoor and outdoor experiments, during which the average position errors have been lower than 0.3 m for paths more than 1 km long