A Frontier Based Multi-Robot Approach for Coverage of Unknown Environments

With the advent of latest technical advancements in the field of robotics, a stage has arrived where autonomous robots are expected to help humans in tasks that are either dangerous or too monotonous such as mining, search and rescue, floor cleaning. All these problems are derivatives of coverage problem wherein the motto is complete coverage of the environment in a time effective manner. Most of the coverage methods developed till date have access to the map prior to exploration and only few of them made use of multiple robots. In view of the drawbacks of the existing approaches, we developed a frontier based multi robot approach for coverage of unknown environments where map building and exploration is done simultaneously. Individual maps from the robots are merged to form a global map. Frontiers which are the boundaries between explored and unexplored areas are identified and the robots are navigated toward frontiers using the proposed exploration strategy. Robot operating System (ROS) is used for implementation and Stage is used for simulating robots and their environments. Simulation results are obtained for proposed approach and are compared with various existing exploration strategies

coExplore: Combining multiple rankings for multi-robot exploration

Multi-robot exploration is a field which tackles the challenge of exploring a previously unknown environment with a number of robots. This is especially relevant for search and rescue operations where time is essential. Current state of the art approaches are able to explore a given environment with a large number of robots by assigning them to frontiers. However, this assignment generally favors large frontiers and hence omits potentially valuable medium-sized frontiers. In this paper we showcase a novel multi-robot exploration algorithm, which improves and adapts the existing approaches. Through the addition of information gain based ranking we improve the exploration time for closed urban environments while maintaining similar exploration performance compared to the state-of-the-art for open environments. Accompanying this paper, we further publish our research code in order to lower the barrier to entry for further multi-robot exploration research. We evaluate the performance in three simulated scenarios, two urban and one open scenario, where our algorithm outperforms the state of the art by 5% overall.Comment: 7 pages, 8 figure

Leader follower pattern formation control using ros for mobile robot application

In this project, the mobile robots with the leader-follower formation control is being created. The formation problem is converted to a trajectory tracking problem and a reference trajectory is generated for each follower. After that, a tracking controller from the literature is applied to drive the robots towards their corresponding desired trajectories and then the formation will be formed as the follower will also move. Our target and objective in this project are to design a mobile robot leader follower with obstacle avoidance while analyze the robot formation control based on the desired position in different environment. In addition, we are also to design a control strategy of the mobile robot formation with obstacle avoidance. In facts, this is the major parts to ensure that all unwanted incident can be avoid after be applied in later. To achieve all the desired objective, a new framework is proposed for implementing the formation control laws on nonholonomic mobile robots based on ROS (Robot Operating System). ROS will be used to be the main system in controlling the hardware and also to create a virtual environment, generate robot model called Turlebot and implement the algorithms such as SLAM. ROS provides some convenient packages with ROS node and the SLAM algorithms that make the formation problem easier to solve. The creation of the hardware parts is using the raspberry pi 3b+ and the OpenCR as the main component while the creation of the virtual environment will be done by using Gazebo and Rviz (ROS Visualization). Our propose work in this project is to design for the turtlebot3 burger equipped with Lidar sensor as the main mobile robot to have the obstacle avoidance and the formation control. The environment of different formation control will be created and will be analyze in this project. As addition, We will create the track and the indoor environment map to simulate all the testing in this project. We will investigate Turtlebot ability to keep the formation with desired velocity. After that, the obstacle avoidance task will be applied to the same Turtlebot to avoid any circumstances that block its way. This Turtlebot soon will be a leader for multiple mobile robots that will follow it as follower with the help of LDS to detect the distance between them with their leader and provide the information for reference trajectory

A New Frontier Based Approach for Multi-Robot Coverage in Unknown Environments

With the emergence of technology in our daily lives, robots are being increasingly used for coverage tasks which were earlier considered too dangerous or monotonous to be performed by humans such as interplanetary exploration and search & rescue. Out of all the multi-robot coverage approaches, the frontier based approach is one of the most widely used. Most of the coverage approaches developed so far, face the issue of frontier duplication and require access to the maps of the environment prior to coverage. In this work, we have developed a new frontier based approach for multi-robot coverage in unknown environments. This new approach is scalable to multiple robots and does not require prior access to the maps. This approach also uses a new frontier allocation and robot coordination algorithm, which reduces the frontier duplication in the robots and improves the efficiency of robot coverage