In the multi-robots system, it's important for a robot to acquire adaptivenavigation rules for reaching the goal and avoiding other robots and obstacles and in the real-timeenvironment. An efficient approach to co...In the multi-robots system, it's important for a robot to acquire adaptivenavigation rules for reaching the goal and avoiding other robots and obstacles and in the real-timeenvironment. An efficient approach to collision-avoidance in multi-robots system is suggested . Itis based on velocity information of moving objects and the distances between the robots and theobstacles in three specified directions and makes the robot navigate adaptively without collisionwith each other in a complicated situation. The effectiveness of algorithm is proved by the severalsimple examples in the physical world.展开更多
This paper presents autonomous docking of an inhouse built resident Remotely Operated Vehicle(ROV),called Rover ROV,through acoustic guided techniques.A novel cage-type docking station has been developed.The docking s...This paper presents autonomous docking of an inhouse built resident Remotely Operated Vehicle(ROV),called Rover ROV,through acoustic guided techniques.A novel cage-type docking station has been developed.The docking station can be placed on a deep-sea lander,taking the Rover ROV to the seafloor.Instead of using vision-based pose estimation techniques and expensive navigation sensors,the Rover ROV docking adopts an ultra-short baseline(USBL)and low-cost inertial sensors to build an adaptive fault-tolerant integrated navigation system.To solve the problem of sonar-based failure positioning,the measurement residuals are exploited to detect measurement faults.Then,an adaptation scheme for estimating the statistical characteristics of noise in real-time is proposed,which can provide robust and smooth positioning results.It is more suitable for a compact and low-cost deep-sea resident ROV.Field experiments have been conducted successfully in the Qiandao Lake and the South China Sea area with a depth of 3000 m,respectively.The experimental results show that the functionality of autonomous docking has been achieved.Under the guidance of the navigation system,the Rover ROV can autonomously and efficiently return to the docking station within a range of 100 m even when the amounts of outliers exist in the acoustic positioning data.These achievements can be applied to current ROVs by an easy retrofit.展开更多
In the present work, autonomous mobile robot（AMR） system is intended with basic behaviour, one is obstacle avoidance and the other is target seeking in various environments. The AMR is navigated using fuzzy logic, n...In the present work, autonomous mobile robot（AMR） system is intended with basic behaviour, one is obstacle avoidance and the other is target seeking in various environments. The AMR is navigated using fuzzy logic, neural network and adaptive neurofuzzy inference system（ANFIS） controller with safe boundary algorithm. In this method of target seeking behaviour, the obstacle avoidance at every instant improves the performance of robot in navigation approach. The inputs to the controller are the signals from various sensors fixed at front face, left and right face of the AMR. The output signal from controller regulates the angular velocity of both front power wheels of the AMR. The shortest path is identified using fuzzy, neural network and ANFIS techniques with integrated safe boundary algorithm and the predicted results are validated with experimentation. The experimental result has proven that ANFIS with safe boundary algorithm yields better performance in navigation, in particular with curved/irregular obstacles.展开更多
文摘In the multi-robots system, it's important for a robot to acquire adaptivenavigation rules for reaching the goal and avoiding other robots and obstacles and in the real-timeenvironment. An efficient approach to collision-avoidance in multi-robots system is suggested . Itis based on velocity information of moving objects and the distances between the robots and theobstacles in three specified directions and makes the robot navigate adaptively without collisionwith each other in a complicated situation. The effectiveness of algorithm is proved by the severalsimple examples in the physical world.
基金financially supported by the National Key R&D Program of China (Grant No. 2017YFC0306402)the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA22040102)
文摘This paper presents autonomous docking of an inhouse built resident Remotely Operated Vehicle(ROV),called Rover ROV,through acoustic guided techniques.A novel cage-type docking station has been developed.The docking station can be placed on a deep-sea lander,taking the Rover ROV to the seafloor.Instead of using vision-based pose estimation techniques and expensive navigation sensors,the Rover ROV docking adopts an ultra-short baseline(USBL)and low-cost inertial sensors to build an adaptive fault-tolerant integrated navigation system.To solve the problem of sonar-based failure positioning,the measurement residuals are exploited to detect measurement faults.Then,an adaptation scheme for estimating the statistical characteristics of noise in real-time is proposed,which can provide robust and smooth positioning results.It is more suitable for a compact and low-cost deep-sea resident ROV.Field experiments have been conducted successfully in the Qiandao Lake and the South China Sea area with a depth of 3000 m,respectively.The experimental results show that the functionality of autonomous docking has been achieved.Under the guidance of the navigation system,the Rover ROV can autonomously and efficiently return to the docking station within a range of 100 m even when the amounts of outliers exist in the acoustic positioning data.These achievements can be applied to current ROVs by an easy retrofit.
文摘In the present work, autonomous mobile robot（AMR） system is intended with basic behaviour, one is obstacle avoidance and the other is target seeking in various environments. The AMR is navigated using fuzzy logic, neural network and adaptive neurofuzzy inference system（ANFIS） controller with safe boundary algorithm. In this method of target seeking behaviour, the obstacle avoidance at every instant improves the performance of robot in navigation approach. The inputs to the controller are the signals from various sensors fixed at front face, left and right face of the AMR. The output signal from controller regulates the angular velocity of both front power wheels of the AMR. The shortest path is identified using fuzzy, neural network and ANFIS techniques with integrated safe boundary algorithm and the predicted results are validated with experimentation. The experimental result has proven that ANFIS with safe boundary algorithm yields better performance in navigation, in particular with curved/irregular obstacles.
