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.

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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

This article deals with path planning of a mobile robot based on a grid map. Essential assumption for path planning is a mobile robot with functional and reliable reactive navigation and SLAM. Therefore, such issues are not addressed in this article. The main body of the article introduces several modifications (Basic Theta*, Phi*) and improvements (RSR, JPS) of A star algorithm. These modifications are focused primarily on computational time and the path optimality. Individual modifications were evaluated in several scenarios, which varied in the complexity of environment. On the basis of these evaluations, it is possible to choose path planning method suitable for individual scenario. © 2014 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of organizing committee of the Modelling of Mechanical and Mechatronic Systems MMaMS 2014. Keywords: path planning, A* algorithm, Basic Theta*, Phi*, Jump Point Search Nomenclature SLAM Simultaneous Localization and Mapping A* A star RSR Rectangular Symmetry Reduction JPS Jump Point Search

Modelling of Mechanical and Mechatronic Systems MMaMS 2014 Path planning with modified A star algorithm for a mobile robot

The cheap work with high precision is very necessary in industry for a long time. Research in robotics gives us opportunity for development of automatically guided vehicle controlled by PLC, which can be easily used for supplement transport inside factory, or even for human transport. Main aim of this work is to show, how to replace expensive industrial sensors with integrated communication interface by simple cheap open-source technology. Our solution is focused on TCP communication between Arduino and PLC. The Arduino is extended to Ethernet shield. It makes possibility to connect third-party devices to PLC and save I/O PLC modules. The Arduino pre-process data from ultrasonic and line-following sensors and combine them into one data packet which is send over the network to PLC server.

Sensoric subsystem of automated guided vehicle: TCP communication between SIMATIC S7 PLC and Arduino

Although it is relatively easy to equip mobile robot with Kinect sensor, implementation of mapping algorithm can be non trivial In this article, we describe sensor device, robot map formats and two main approaches to 3D reconstruction, problem closely connected to SLAM mapping problem with Kinect sensor We experimentally evaluate reference implementations of both algorithms, compare their results and discuss published and possible improvements of both approaches

3D map reconstruction with sensor kinect: Searching for solution applicable to small mobile robots

The objective of this paper was to analyze several approaches to the probabilistic modeling of Hokuyo-type laser rangefinder (LRF). These models, which reflect mostly the mixed pixels, beam width, signal, and impulse noise, were compared mutually. Motivation for creating these models was the failure of existing LRF models to faithfully represent the features of sensed environment. Moreover, the characteristics of each particular model were highlighted, and their suitability for various applications was determined. This paper also dealt with data fusion by selected model and its representation in the occupancy grid. This was based on the classical Bayes’ rule, which was adapted for the desired characteristics of data fusion. Finally, in order to improve data from the sensor, data pre-processing was proposed. Mentioned data pre-processing was proposed with the emphasis on the elimination of impulsive noise. The overall concept of data processing from the LRF can be regarded as versatile and robust.

Martin Kajan

Papers

Path Planning with Modified a Star Algorithm for a Mobile Robot

Modelling of Mechanical and Mechatronic Systems MMaMS 2014 Path planning with modified A star algorithm for a mobile robot

Sensoric subsystem of automated guided vehicle: TCP communication between SIMATIC S7 PLC and Arduino

3D map reconstruction with sensor kinect: Searching for solution applicable to small mobile robots

Versatile Approach to Probabilistic Modeling of Hokuyo UTM-30LX