A new fuzzy intelligent obstacle avoidance control strategy for wheeled mobile robot
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Obstacle avoidance is the basic requirement for any autonomous mobile robot. Fuzzy intelligent obstacle avoidance strategy is proposed in this paper for the wheeled mobile robot tracking a target in the environment with obstacles, which is composed of two fuzzy logic controllers and an intelligent coordinator. Run-to-goal fuzzy controller makes the robot approach the target when there are no obstacles in the environment; Fuzzy obstacle controller will generate obstacle avoidance commands according to target orientation information and obstacle information when the robot detecting obstacles via its onboard sensors. Intelligent coordinator is designed to coordinate the two actions mentioned above to generate robot's ultimate control command. Ultimately, the robot tracks the target and realizes obstacle avoidance meanwhile. Simulations and experiments on robot platform validate the effectiveness proposed by the paper.Keywords:
Obstacle avoidance
The pilotless fruit-transportation gyrocar works in the economic forest, avoiding the obstacle on the rail is the prerequisite of its safe working. An ultrasonic obstacle avoidance system of fruit-transportation gyrocar based on ARM embedded system is introduced in this article. The functions of the system are implemented. It could make the gyrocar stop when detect an obstacle and sends the information of obstacle to the monitoring client through GPRS. Through the test, the ultrasonic obstacle avoidance system performs well and reliable.
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This paper addresses the obstacle avoidance problem in difficult scenarios that usually are dense, complex and cluttered. The proposal is a method called the obstacle-restriction. At each iteration of the control cycle, this method addresses the obstacle avoidance in two steps. First there is procedure to compute instantaneous subgoals in the obstacle structure (obtained by the sensors). The second step associates a motion restriction to each obstacle, which are managed next to compute the most promising motion direction. The advantage of this technique is that it avoids common limitations of previous obstacle avoidance methods, improving their navigation performance in difficult scenarios. Furthermore, we obtain similar results to the recent methods that achieve navigation in troublesome scenarios. However, the new method improves their behavior in open spaces. The performance of this method is illustrated with experimental results obtained with a robotic wheelchair vehicle.
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Today, many industries are using various technology due to their high level of performance and reliability. The “real time obstacle avoidance” deals with detection and avoidance of various obstacle found in an environment. Obstacle avoidance may be divided into two parts, obstacle detection and avoidance control. For obstacle detection and avoidance, requires the integration of many sensors according to their task. Some sensing devices used for obstacle detection are infrared sensor and ultrasonic sensor. It has an infrared sensor which are used to sense the obstacle coming in between the path. It will move in particular direction and avoid the obstacle which is coming in its path.
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To adapt the autonomous level of agents in current, and to perform the advantages of multi-agent in air combat, the form of manned/unmanned aircraft cooperative system has gradually become a hot topic. To solve the issue of three-dimensional (3D) real-time obstacle avoidance, the 3D maneuvering obstacle model is established firstly based on the traditional velocity obstacle method. Then the flight mode is selected and the optimal obstacle avoidance plane is determined by setting the Right-of-way rules when the system encountering obstacles. Finally, the difference of obstacle avoidance plane, the feasibility of avoiding maneuvering obstacle and the effectiveness of obstacle avoidance of cooperative system are verified by several flight simulations. The results show that the proposed method can realize the avoidance of 3D maneuvering obstacle for manned/unmanned aircraft cooperative system safely and efficiently.
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This paper treats the safety issues in coordinated transportation of an object via multiple Unmanned Aerial Vehicles with Manipulator Systems (UAVMS); in particular, the case of obstacle avoidance is considered. The proposed paradigm is based on the so-called Null-Space-based Behavioral (NSB) control approach, that allows to achieve multiple tasks simultaneously. Two different scenarios of bar transportation using multi-UAVMSs have been developed, tested and compared in simulation: in the first scenario, the obstacle avoidance is achieved at the coordination level, where the controller allows the whole system (UAVMSs and bar) to circumnavigate the obstacle; while in the second scenario only the UAVMS closest to the obstacle modifies its trajectory to overcome the obstacle by keeping the desired trajectory of the bar unchanged.
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The problems of formation and obstacle avoidance control for multi-agent networks were considered in this paper.The goal was to make the agents reach a desired formation while avoiding collision with obstacle.Proper potential function concerned with target,obstacle and structure of the formation,was chosen to design a novel distributed control algorithm.To solve the problem that agents could not effectively avoid the obstacle in dynamic environment,a new velocity potential was deduced,in which the agents could escape from a moving obstacle quickly.One advantage of the algorithm was that it was easy to implement,because control was based on general rules which determined behaviors of all agents.Simulations were provided to verify the effectiveness of the proposed approach.
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Aiming at the research of cooperative obstacle avoidance in tracing based on the traditional flocking model,it was improved by us and added the Steer to Avoid obstacle avoidance method.The improved model has a high efficiency in avoiding static obstacle.We applied this model to mobile obstacle environment.It turns out that the obstacle avoi-dance efficiency is very low,because it is possible that WSN nodes and obstacle stay relatively static in the process of avoiding obstacle.Aiming at this drawback,this article proposed a new cooperative obstacle avoidance approach by improving the Steer to Avoid method.When the velocity of the obstacle is close to nodes' velocity,WSN nodes will be moving in the reverse direction of the obstacle.And we introduced obstacle moving prediction.Simulation results show that the proposed model,compared with the traditional model,has a marked increase on average speed and time efficiency.Also,it can succeed in avoiding mobile convex obstacles in unknown environment.
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In order to solve the problem of intelligent obstacle avoidance when an unmanned surface vehicle navigates autonomously in a complex marine environment, the obstacle avoidance is divided into stationary obstacle avoidance and dynamic obstacle avoidance. Based on the ant colony algorithm, the local path planning of the simplified model of the unmanned surface vehicles is carried out to achieve the static collision avoidance. And in accordance with the Convention on the International Regulations for Preventing Collisions at Sea (COLREGS), a dynamic obstacle model is established and calculated to obtain the changes of the speed and course of the unmanned surface vehicles under different encounters. It is shown through the simulations that the proposed approach considering multiple factors can achieve the automatic collision avoidance.
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Obstacle detection and avoidance is an essential part in the field of autonomous vehicles. In this paper, we propose a novel methodology for obstacle detection and avoidance for the rapidly-developing category of autonomous bicycles. This comprises the bicycle-specific design of our Light Detection And Ranging(LiDAR)-based sensor system and our obstacle detection technique, including the segmentation of the surrounding environment 3D point cloud into discrete obstacle clusters within the bicycle's path and a method for detecting areas containing liquids on the road surface. Moreover, our obstacle avoidance technique is introduced, consisting of a local path planning and a path following part, enabling our bicycle to avoid the closest obstacle lying on the bicycle's user-defined route. The proposed method takes into account the unique dynamic characteristics of bicycles, and the results of the simulation and outdoor experiment confirm its efficacy and promising behavior.
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Ranging
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