Research on Improved Artificial Potential Field Ship-ice Collision Avoidance Method

Formation coordination can improve the overall performance of unmanned aerial vehicle (UAV) systems, so it is important to realize coordinated formation control. To solve the problems of ineffective internal collision avoidance and communication distance maintenance in existing formation control methods, a UAV formation control algorithm based on an improved artificial potential field and consensus is proposed. First, an improved artificial potential field obstacle avoidance method is used to solve the problems of collision avoidance and communication distance maintenance within the formation by setting a communication risk zone and a collision risk zone and by defining the dynamic adjustment parameters of the inter‐UAV virtual force to improve the traditional artificial potential field method. Second, a time integrating factor is introduced, and an improved consensus‐based formation control method is employed to overcome the problem of the artificial potential field method falling into the local optimum easily. Simulation experiments were designed to analyse the trends of the UAV formation motion trajectory, inter‐UAV relative distance, attitude, and formation time. The analysis results show that the method can make the UAV formation consistent with the flight trajectory of the intended formation, solving the problems of collision avoidance and communication distance maintenance within the UAV formation.

As a simple and effective method, artificial potential field method is often used in robot path planning. Based on this, an improved artificial potential field model is proposed to solve the local minimum problem by using a subgoal strategy. In order to show the subgoal adaptive selection feature of the robot, an obstacle potential field function is established and the effectiveness of the adaptive feature is verified by path planning simulation. A double closed-loop control strategy is adopted to track the trajectory planned by the improved artificial potential field method, and simulation results show that the improved artificial potential method is reliable and the robot can well track the trajectory under the action of the controller.

Aiming at the problem that the collision avoidance process of the UVA is the existence of local minima by using the artificial potential field method, a compound vector artificial potential field method is proposed based on the virtual structure and the leader-follower control strategy in the three-dimensional space, which can avoid the obstacle effectively and then track the motion target. The attractive force of the artificial potential field can guide the virtual leader to track the target. At the same time, the follower tracks the leader to keep the formation flight. The effect of the repulsive force can avoid the collision between any two UAVs and arrange the followers evenly distributed on the spherical surface. Moreover, the follower's specific order and position are not required. The collision path of the UAV formation depends on the artificial potential field with the two composite vectors, every UAV can choose the optimal path to avoid the obstacle and reconfigure the regular triangle formation flight after passing the obstacle. The simulation experiment verifies the validity and feasibility of the proposed the collision avoidance control algorithm and provides an idea for the collision avoidance of the Multi-UAV formation.

This paper addresses a local minima problem for multiple unmanned aerial vehicles (UAVs) in the process of collision avoidance by using the artificial potential field method, thereby enabling UAVs to avoid the obstacle effectively in 3-D space. The main contribution is to propose a collision avoidance control algorithm based on the virtual structure and the “leader–follower” control strategy in 3-D space that can avoid the obstacle effectively and then track the motion target. The three UAVs constitute the regular triangular formation as the control object, the virtual leader flight trajectory as the expected path, the obstacles as the simplified cylinders, and the artificial potential fields around them as approximately spherical surfaces. The attractive force of the artificial potential field can guide the virtual leader to track the target. At the same time, the follower tracks the leader to maintain the formation flight. The effect of the repulsive force can avoid the collision between the UAVs and arrange the followers such that they are evenly distributed on the spherical surface. Moreover, the follower’s specific order and position are not required. The collision path of the UAV formation depends on the artificial potential field with the two composite vectors, and every UAV may choose the optimal path to avoid the obstacle and reconfigure the regular triangular formation flight after passing the obstacle. The effectiveness of the proposed collision avoidance control algorithm is fully proved by simulation tests. Meanwhile, we also provide a new concept for multi-UAV formation avoidance of an obstacle.

Aiming at the local minimum point problem in an artificial potential field based on a safe distance model, this article proposes an algorithm for active obstacle avoidance path planning and tracking of autonomous vehicles using an improved artificial potential field. First, a possible road operating condition in which the artificial potential field based on the safety-distance model falls into a local minimum point is studied. Subsequently, an improved artificial potential field method is proposed by introducing the second virtual target attraction potential field, which successfully overcomes the local minimum point problem. Second, a model for autonomous vehicle active obstacle avoidance path planning and tracking based on the improved artificial potential field is established. Finally, MATLAB/CarSim co-simulations were performed under the road conditions of constant- and variable-velocity obstacle vehicles. The simulation results demonstrate that the improved artificial potential field method can effectively solve the local minimum point problem of the artificial potential field based on the safe distance model. Additionally, the safety and stability of autonomous vehicle active obstacle avoidance are improved.

It is a hot topic in the field of road landscape planning technology that a mobile robot can quickly and safely find an optimal path in a multi-obstacle environment. In path planning, in light of the problems of poor cooperation and slow convergence of ant colony algorithm in a known environment, the existing potential field method in the local path environment focuses on avoiding dynamic obstacles but cannot guarantee an optimal path. This study provides a new fusion algorithm for path planning optimization in both static and dynamic environments. Firstly, to prevent slipping into a local optimum, create a pheromone diffusion model and adaptively tweak the population information entropy factor to speed up the convergence speed of the Adaptive Ant Colony Optimization (AACO) algorithm. Secondly, on the basis of the globally planned path, by designing the local stability detection and escape functions, the Improved Artificial Potential Field (IAPF) method is utilized to solve the problem of unreachable destination. Finally, we conduct simulation experiments through MATLAB to compare the indicators for evaluating paths, it verifies that the fusion algorithm proposed in this research has obvious advantages in path planning in both static and dynamic environments.KeywordsPath planningAdaptive ant colony optimizationPopulation information entropyImproved artificial potential field

In this paper, artificial potential field is applied to real-time path planning for obstacle avoidance of manipulators. In this approach, a collision-free path from the initial state to target is planned in three-dimensional space. Artificial potential field is widely used in obstacle avoidance for manipulators, with the advantages of simple structure and real-time performance, but there is a local minima problem in this method. Firstly, the artificial potential field method is used to determine the joint-space path of manipulator, and the path is smoothed to ensure the flexibility of joint-motion. Secondly, the local minima problem is decomposed into two categories: unreachable target and local minima. Virtual obstacles and targets are set to avoid the problem. Finally, regarding time as the optimization target, simulated annealing algorithm is used to search the optimal parameters of artificial potential field. The simulation results verify the effectiveness and adaptability of the algorithm.

The artificial potential field method is frequently employed for obstacle avoidance both of mobile robots and of manipulator arms. This paper extends previous results for planar problems to the general n-dimensional case. The complexity is reduced by projecting the n-dimensional workspace onto a 2D subspace called operation plane. Furthermore, only the closest obstacles are taken into account when designing the artificial potential field. Still, global convergence is achieved. The methodology is illustrated with several numerical examples.

Wireless ultraviolet light MIMO assisted UAV direction perception and collision avoidance method

This paper presents a modified artificial potential field (APF) based method for an Autonomous Surface Vessel (ASV) obstacles avoidance in a dynamic riverine environment. The APF method is combined with a balance control scheme to achieve river tracking and obstacles avoidance simultaneously. The APF method is further modified modification to comply with marine collision avoidance regulations (COLREGs). The overtaking and head-on scenarios are simulated in MATLAB platform. The simulation results are compared with other APF methods to prove that the proposed method is efficient for the ASV riverine navigation.

Polar regions have a profound impact on global climate change, because polar regions are one of the world’s largest sources of cold. Sea ice is the main influencing factor in the polar regions, which has a great influence on the heat transfer, which in turn affects the global climate system. In the past two decades, Arctic sea ice has decreased year by year, while Antarctic sea ice has increased. The use of passive satellite remote sensing data for long-term observation and analysis of polar sea ice will provide an important theoretical basis for studying global climate change and an important data source for polar sea ice research. This study uses the data of the Antarctic and Arctic sea ice density data from 1998 to 2018 to compare and analyze the changes in time and space to find out the changes of the sea ice in the south and Arctic. Using the SSM / I data of the US National Defense Meteorological Satellite and the NASA TEAM algorithm, the sea ice data from 1998 to 2018 was compared and analyzed. The specific process is to use the NASA TEAM algorithm to invert the Arctic and Arctic sea ice, obtain multi-year ice, one-year ice, and overall sea ice density data, and then determine the sea ice area. Through comparative analysis, it is found that the area of Antarctic sea ice is significantly larger than that of the North Pole, and the change trend of the two is similar. The downward trend is greater than that of the South Pole; the total annual ice volume of the South Pole is greater than that of the North Pole, both of which have an upward trend, and the Arctic has a greater increase; the overall sea ice has fallen, and the multi-year ice has decreased while the annual ice has increased. Sea ice has a tendency to transform from multi-year ice to one-year ice; Antarctic multi-year ice is mainly distributed in the Weddell Sea, with stable areas accounting for 60% of the multi-year ice area; Antarctica is dominated by one-year ice, and one-year ice stable area accounts for one 80.1% of the total annual ice area; Arctic multi-year ice mainly exists in the central area of the Arctic Ocean. The Arctic multi-year ice stable area only accounts for 35.06%; the Arctic one-year ice is mainly distributed around the multi-year ice periphery, and the stable existence area accounts for the total annual ice area 48.5%.

Investigating the occurrence and accumulation of perfluoroalkylated substances and other persistent organic pollutants in snow and ice of the Earth’s Polar regions

A novel model predictive artificial potential field based ship motion planning method considering COLREGs for complex encounter scenarios

A two-stage dynamic collision avoidance algorithm for unmanned surface vehicles based on field theory and COLREGs

This study shows that ERTS-l, launched by the U.S. National Aeronautics and Space Administration in July 1972, can be used to make synoptic observations of dynamic changes in arctic sea ice .... Each data swath of ERTS-l is 185 kilometres wide at the surface and is repeated once every 18 days. ... Because of a near-polar orbit, this sidelap increases to over 80 per cent at arctic latitudes. As a consequence of this large sidelap, the tracking of individual ice features for periods up to 5 or 6 days is permitted. The ERTS-1 Multispectral Scanner Subsystem (MSS) records data by simultaneously scanning across the satellite track in 4 spectral bands. The wavelength limits of the 4 bands are: green (0.5-0.6 µm), red (0.6-0.7 µm), and two near infrared bands (0.7-0.8 µm and 0.8-1.1 µm). The nominal spatial resolution for all 4 bands is 80 metres. A standard ERTS-1 photographic format has an image scale of nearly 1:1,000,000, which is convenient for direct comparison with available maps. Hendriksen Strait, the passage between Amund Ringnes Island and Cornwall Island at about 77°45' N and 95°00' W constituted the study area; it is in the Queen Elizabeth Islands of Arctic Canada, and is one of the most enticing and promising areas of recent oil and gas strikes. ... during a 6-day period from 23 to 28 August, ERTS-1 provided 5 days of coverage of Hendriksen Strait. Various types of sea ice can be identified in the ERTS-l imagery (0.6-0.7 µm band) .... In such a sequence of observations, a number of sea ice changes with time are detectable. Changes in position of individual ice floes can easily be translated to velocity. A number of ice floes were tracked over the 5-day period and their velocities calculated. The average velocity for ice floe movement was 8.5 kilometres/day .... ERTS-l can be used to study ice floe morphology and dynamics in the Beaufort Sea at time scales of several days to months. Repeated observations of individual ice floes such as those available here will also allow calculation of the ablation of the ice mass, in this case the decrease of surface area with time. ... The ice cover, i.e. the relative amount of sea ice present in a given area, is important for shipping purposes and air-sea interaction processes. The ice cover in Hendriksen Strait on 23 August was approximately 7/10, decreasing to 2/10 by 28 August. This type of sea ice change is easily observed from ERTS-1 .... In regard to the delineation of navigation routes through sea ice, the detection of active melting on the surface of the ice would indicate areas likely to be ice free in the near future. ERTS-1 has the ability to do this through observations of reflectance variability both temporally and spectrally. The second method of observing the sea ice reflectance change is provided by comparing two separate images made at the same time but in different spectral bands. ... Because the absorption of solar radiation by water is much greater in the near infrared than in the visible portion of the spectrum, the lower reflectance is again probably due to the presence of melt-water on the surface of the ice. Thus sea ice with water on it, even in very thin layers, will show a considerable difference in reflectance between these spectral bands of observation. ... Temporal and spectral observations of reflectance variations afforded by ERTS-l thus make it possible to locate areas of sea ice that are in varying stages of melting and breakup. The results presented here demonstrate that for high latitudes, ERTS-1 will provide overlapping coverage on sequential days that will allow observation of dynamic changes in the polar regions. In addition, route planning for shipping in the Arctic should benefit from frequent observations of sea ice movement and reflectance variations of the type obtainable from ERTS-l. Projected further, sea ice observations from ERTS-l over a period of years in the Arctic Islands should aid in the placement of offshore oil-drilling structures. Reflectance measurements over this period will also increase our understanding of the heat balance in the polar regions. Finally, ERTS-l observations of the amount of ice cover versus the amount of open water will be important in determining boundary conditions for future use in models of the global heat balance.