UAV assistance paradigm: State-of-the-art in applications and challenges

A constrained A* approach towards optimal path planning for an unmanned surface vehicle in a maritime environment containing dynamic obstacles and ocean currents

This paper proposes an improved ant colony algorithm to achieve efficient searching capabilities of path planning in complicated maps for mobile robot. The improved ant colony algorithm uses the characteristics of A* algorithm and MAX-MIN Ant system. Firstly, the grid environment model is constructed. The evaluation function of A* algorithm and the bending suppression operator are introduced to improve the heuristic information of the Ant colony algorithm, which can accelerate the convergence speed and increase the smoothness of the global path. Secondly, the retraction mechanism is introduced to solve the deadlock problem. Then the MAX-MIN ant system is transformed into local diffusion pheromone and only the best solution from iteration trials can be added to pheromone update. And, strengths of the pheromone trails are effectively limited for avoiding premature convergence of search. This gives an effective improvement and high performance to ACO in complex tunnel, trough and baffle maps and gives a better result as compare to traditional versions of ACO. The simulation results show that the improved ant colony algorithm is more effective and faster.

/pdf/mobile-robot-path-planning-based-on-ant-colony-algorithm-3g8h4bdcis.pdf

Mobile Robot Path Planning Based on Ant Colony Algorithm With A* Heuristic Method.

Advancing an efficient coverage path planning in robots set up for application such as cleaning, painting and mining are becoming more crucial. Such drive in the coverage path planning field proposes numerous techniques over the past few decades. However, the proposed approaches were only applied and tested with a fixed morphological robot in which the coverage performance was significantly degraded in a complex environment. To this end, an A-star based zigzag global planner for a novel self-reconfigurable Tetris inspired cleaning robot (hTetro) presented in this paper. Unlike the traditional A-star algorithm, the presented approach can generate waypoints in order to cover the narrow spaces while assuming appropriate morphology of the hTtero robot with the objective of maximizing the coverage area. We validated the efficiency of the proposed planning approach in the Robot Operation System (ROS) Based simulated environment and tested with the hTetro robot in real-time under the controlled scenarios. Our experiments demonstrate the efficiency of the proposed coverage path planning approach resulting in superior area coverage performance in all considered experimental scenarios.

Modified A-Star Algorithm for Efficient Coverage Path Planning in Tetris Inspired Self-Reconfigurable Robot with Integrated Laser Sensor.

The unmanned aerial vehicle (UAV) route planning problem mainly centralizes on the process of calculating the best route between the departure point and target point as well as avoiding obstructions on route to avoid collisions within a given flight area A highly efficient route planning approach is required for this complex high dimensional optimization problem However, many algorithms are infeasible or have low efficiency, particularly in the complex three-dimensional (3d) flight environment In this paper, a modified sparrow search algorithm named CASSA has been presented to deal with this problem Firstly, the 3d task space model and the UAV route planning cost functions are established, and the problem of route planning is transformed into a multi-dimensional function optimization problem Secondly, the chaotic strategy is introduced to enhance the diversity of the population of the algorithm, and an adaptive inertia weight is used to balance the convergence rate and exploration capabilities of the algorithm Finally, the Cauchy-Gaussian mutation strategy is adopted to enhance the capability of the algorithm to get rid of stagnation The results of simulation demonstrate that the routes generated by CASSA are preferable to the sparrow search algorithm (SSA), particle swarm optimization (PSO), artificial bee colony (ABC), and whale optimization algorithm (WOA) under the identical environment, which means that CASSA is more efficient for solving UAV route planning problem when taking all kinds of constraints into consideration

https://www.mdpi.com/1424-8220/21/4/1224/pdf

A Modified Sparrow Search Algorithm with Application in 3d Route Planning for UAV.

Path Planning with Modified a Star Algorithm for a Mobile Robot

Visual Localization of Mobile Robot Using Artificial Markers

The paper presents localization method for mobile robots with use of artificial markers deployed to an environment. A specialty of the markers is that the position and rotation of the camera relative to the marker can be determined from only one marker. Fur ther in the paper, some experiments are described. The results prove that this system can be reliably employed in visual localization of mobile robots. © 2014 The Authors. Published by Elsevier Ltd. P eer-review under responsibility of organizing committee of the Modelling of Mechanical and Mechatronic Systems MMaMS 2014.

Modelling of Mechanical and Mechatronic Systems MMaMS 2014 Visual localization of mobile robot using artificial markers

Active ranging sensors are the most popular sensors in mobile robotics. One of them, laser rangefinder, has many advantages over other ranging sensors. Despite its considerably high costs, it is a very accurate, reliable and high-speed sensor. Data from laser rangefinder can be used in many ways. This paper shows some techniques that can be useful in solving tasks such as localization, environmental mapping or navigation. Our approach is based on data pre-processing, using a raw filter as well as a smooth filter. Raw filter allows for reduction of missing and invalid measurements and smooth filter smoothes up the data, so the shape of obstacles can be captured more precisely. In this manner, modified data can be used in further tasks, two of which are presented here: detection of extremes and environmental mapping. Detection of extremes covers corners and discontinuities detection. The result of environmental mapping is a global metric map of the environment. Finally, a short analysis of our future work is presented.

/pdf/some-applications-of-laser-rangefinder-in-mobile-robotics-p5yiylyk6p.pdf

Some applications of laser rangefinder in mobile robotics

The article deals with a novel approach to reactive navigation. A proposed reactive navigation is based on the Vector Field Histogram (VFH) method, which is easily modifiable. The biggest advantage...

Ladislav Jurišica

Papers

Path Planning with Modified a Star Algorithm for a Mobile Robot

Visual Localization of Mobile Robot Using Artificial Markers

Modelling of Mechanical and Mechatronic Systems MMaMS 2014 Visual localization of mobile robot using artificial markers

Some applications of laser rangefinder in mobile robotics

Vector Field Histogram* with look-ahead tree extension dependent on time variable environment: