An improved PSO algorithm for smooth path planning of mobile robots using continuous high-degree Bezier curve

With the development of micro-electromechanical systems (MEMS), miniaturized, low-power and low-cost inertial measurement units (IMUs) have been widely integrated into mobile terminals and smart wearable devices. This provides the prospect of a broad application for the inertial sensor-based pedestrian dead-reckoning (IPDR) systems. Especially for indoor navigation and indoor positioning, the IPDR systems have many unique advantages that other methods do not have. At present, a large number of technologies and methods for IPDR systems are proposed. In this paper, we have analyzed and outlined the IPDR systems based on about 80 documents in the field of IPDR in recent years. The article is structured in the form of an introduction-elucidation-conclusion framework. First, we proposed a general framework to explore the structure of an IPDR system. Then, according to this framework, the IPDR system was divided into six relatively independent sub-problems, which were discussed and summarized separately. Finally, we proposed a graph structure of IPDR systems, and a sub-directed graph, formed by selecting a combined path from the start node to the end node, skillfully constitutes a technical route of one specific IPDR system. At the end of the article, we summarized some key issues that need to be resolved before the IPDR systems are widely used.

A Survey of the Research Status of Pedestrian Dead Reckoning Systems Based on Inertial Sensors

Developing an evacuation evaluation model for offshore oil and gas platforms using BIM and agent-based model

Many missions require unmanned surface vehicles to operate in complex environments over large distances. Marine environments are dynamic in nature and change over time as a result of tides, weather, and environmental restrictions. As a result, the available free traversal space for a marine vehicle in the given map can change over time. This requires the marine vehicle to dynamically generate and update the traversal map to represent the free space. This paper presents techniques for speeding up A* search on the nodes of visibility graphs. We use a quadtree representation of the marine environment to enable the algorithm to efficiently compute the nodes of the visibility graphs. We have developed an admissible heuristic that considers the large islands while estimating cost-to-go, and provide better estimates than a Euclidean distance-based heuristic. Due to the large size of the marine environment, the branching factor of the search tree can become large and reduce the efficiency of the path planner. We have developed an approach that focuses the search by only considering the child nodes lying in the local region around each node. Our experiments demonstrate that by focusing the search, we can reduce the computational time without significantly sacrificing the optimality of the computed path. We also present an extension to the algorithm for handling dynamic environments with time-varying free spaces. We incorporated the depth charts developed by the National Oceanic and Atmospheric Administration (NOAA), Silver Spring, MD, USA, along with the tide predictions to estimate the time-varying free space that can be used by the planner.

Long-Distance Path Planning for Unmanned Surface Vehicles in Complex Marine Environment

This paper proposes a new flight path planning algorithm that finds collision-free, optimal/near-optimal and flyable paths for unmanned aerial vehicles (UAVs) in three-dimensional (3D) environments with fixed obstacles. The proposed algorithm significantly reduces pathfinding computing time without significantly degrading path lengths by using space circumscription and a sparse visibility graph in the pathfinding process. We devise a novel method by exploiting the information about obstacle geometry to circumscribe the search space in the form of a half cylinder from which a working path for UAV can be computed without sacrificing the guarantees on near-optimality and speed. Furthermore, we generate a sparse visibility graph from the circumscribed space and find the initial path, which is subsequently optimized. The proposed algorithm effectively resolves the efficiency and optimality trade-off by searching the path only from the high priority circumscribed space of a map. The simulation results obtained from various maps, and comparison with the existing methods show the effectiveness of the proposed algorithm and verify the aforementioned claims.

https://www.mdpi.com/2079-9292/7/12/375/pdf

A Fast Global Flight Path Planning Algorithm Based on Space Circumscription and Sparse Visibility Graph for Unmanned Aerial Vehicle

FastSLAM is a popular framework which uses a Rao-Blackwellized particle filter to solve the simultaneous localization and mapping problem (SLAM). However, in this framework there are two important potential limitations, the particle depletion problem and the linear approximations of the nonlinear functions. To overcome these two drawbacks, this paper proposes a new FastSLAM algorithm based on revised genetic resampling and square root unscented particle filter (SR-UPF). Double roulette wheels as the selection operator, and fast Metropolis-Hastings (MH) as the mutation operator and traditional crossover are combined to form a new resampling method. Amending the particle degeneracy and keeping the particle diversity are both taken into considerations in this method. As SR-UPF propagates the sigma points through the true nonlinearity, it decreases the linearization errors. By directly transferring the square root of the state covariance matrix, SR-UPF has better numerical stability. Both simulation and experimental results demonstrate that the proposed algorithm can improve the diversity of particles, and perform well on estimation accuracy and consistency.

An Improved FastSLAM Algorithm Based on Revised Genetic Resampling and SR-UPF

Path planning is an essential and inevitable problem in robotics. Trapping in local minima and discontinuities often exist in local path planning. To overcome these drawbacks, this paper presents a smooth path planning algorithm based on modified visibility graph. This algorithm consists of three steps: (1) polygons are generated from detected obstacles; (2) a collision-free path is found by simultaneous visibility graph construction and path search by A∗ (SVGA); (3) the path is smoothed by B-spline curves and particle swarm optimization (PSO). Simulation experiment results show the effectiveness of this algorithm, and a smooth path can be found fleetly.

A smooth local path planning algorithm based on modified visibility graph

For path planning algorithms based on visibility graph, constructing a visibility graph is very time-consuming. To reduce the computing time of visibility graph construction, this paper proposes a novel global path planning algorithm, bidirectional SVGA (simultaneous visibility graph construction and path optimization by A?). This algorithm does not construct a visibility graph before the path optimization. However it constructs a visibility graph and searches for an optimal path at the same time. At each step, a node with the lowest estimation cost is selected to be expanded. According to the status of this node, different through lines are drawn. If this line is free-collision, it is added to the visibility graph. If not, some vertices of obstacles which are passed through by this line are added to the OPEN list for expansion. In the SVGA process, only a few visible edges which are in relation to the optimal path are drawn and the most visible edges are ignored. For taking advantage of multicore processors, this algorithm performs SVGA in parallel from both directions. By SVGA and parallel performance, this algorithm reduces the computing time and space. Simulation experiment results in different environments show that the proposed algorithm improves the time and space efficiency of path planning.

/pdf/a-global-path-planning-algorithm-based-on-bidirectional-svga-2p7zc3plkl.pdf

A Global Path Planning Algorithm Based on Bidirectional SVGA

A path planning algorithm for mobile robot based on edge-cloud collaborative computing

To monitor the discharge of water pollutants from vessels, a monitoring system for the discharge of water pollutants from vessels has been established on the Yangtze River. The system generates tens of thousands of ship wastewater pollutant data every day. The analysis and visualization of wastewater pollutant discharge data can help the monitoring department to grasp the discharge situation and improve the accuracy of supervision. This system extracts the data to the data warehouse in real-time based on the data extraction technology, improves the query efficiency based on the three-level storage architecture, makes real-time pollutant data statistics based on the stream computing technology, and realizes the visual display of the data based on the front-end and back end-separation technology. The system has been applied in the maritime supervision department to provide a data basis for vessel wastewater pollutant supervision and decision-making.

https://iopscience.iop.org/article/10.1088/1742-6596/2400/1/012004/pdf

Taizhi Lv

Papers

An Improved FastSLAM Algorithm Based on Revised Genetic Resampling and SR-UPF

A smooth local path planning algorithm based on modified visibility graph

A Global Path Planning Algorithm Based on Bidirectional SVGA

A path planning algorithm for mobile robot based on edge-cloud collaborative computing

Design and Implementation of Wastewater Pollutant Data Analysis and Visualization System for Vessels