Turning Locomotion Analysis and Performance Evaluation for a Spherical Underwater Robot

In this paper, a spherical underwater robot is proposed that uses six degree of freedom thrust allocator to determine the magnitude and the direction of thrust required for each water-jetted bilge pump thruster to create force and moment equilibrium. However, in order to ensure safe operation of the underwater robot it is equipped with redundant thruster configuration and therefore is over-actuated. Therefore, the choice of a particular solution for thrust allocation is found using an optimization process. In this work, the thrust allocation problem is formulated as an optimization problem, with an objective to minimize the total power consumption of the spherical underwater robot. A set of all physically realizable surge, sway and heave force for the i <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> thruster is called as its Attainable Thrust Region (ATR). Since the thrust force produced by each thruster is restricted to its ATR, the power consumption of underwater robot is determined by establishing a relationship between the power consumption and the thrust of an individual bilge pump. The formulated optimal thrust allocation problem is solved using Mincon (Sequential Quadratic Programming) and GA (Genetic Algorithm) optimization algorithm. The percentage savings in total power consumption for thruster system using the GA as compared to Mincon method is 33.82 %.

Considering the complicated disturbance in underwater circumstance, usually it is difficult to solve the control problem when the robot changes its motion state or it is subject to ocean currents, its performance deteriorates since the fixed set of parameters is no longer valid for the new conditions. Thus, in this paper, an auto-tune PID (Proportional + Integral + Derivative)-like controller based on Neural Networks is applied to our amphibious spherical underwater robot, which has a great advantage on processing online for the robot due to their nonlinear dynamics. The Neural Networks (NN) plays the role of automatically estimating the suitable set of PID gains that achieves stability of the system. The NN adjusts online the controller gains that attain the smaller position tracking error. The performance of the NN-based controller is investigated in ADAMS and MATLAB cooperative simulation. The velocity of the spherical robot can be controlled to precisely track desired trajectory in body-fixed coordinate system. Additionally, real time experiments on our underwater spherical robot are conducted to show the effectiveness of the algorithm.

Aiming at multi robot cooperation application requirements of our small-scaled underwater spherical robots, a cooperative formation control system with static and dynamic target rounding up was proposed and studied in this paper. Considering the complex underwater environment and kinematic modeling of the robot, a simplified kinematic model of underwater spherical robot with horizontal and vertical motion was established. Given the environmental disturbances in practical underwater scenarios, an adaptive control algorithm was designed to control the underwater spherical robot, which has good robustness and adaptability. To handle the application requirement of static and dynamic target rounding up with multi robots, the path planning strategy of multi robot was proposed, the modeling of static and dynamic target rounding up was analyzed and optimized, and a controller based on linear quadratic regulator method was also designed to realize static/dynamic target rounding up with multi robots. In addition, underwater target rounding up experiments with two or three spherical robots were conducted to test the feasibility and performance of the proposed formation control system, and the experimental results confirmed the validity of the proposed system. This study may inspire future underwater multi robot cooperation that have properties of high efficiency, wide range and multi tasks and has low environmental interference of aquatic environments.

In this paper, a spherical underwater robot uses optimal thrust allocator to determine the magnitude and the direction of thrust required for each water-jetted bilge pump thruster to create force and moment equilibrium. However, in order to ensure safe operation of the underwater robot it is equipped with redundant thruster configuration and therefore is over-actuated. Therefore, the choice of a particular solution for thrust allocation is found using an optimization process. In this work, the thrust allocation problem is formulated as an optimization problem, with an objective to minimize the total power consumption of the spherical underwater robot. The power consumption of underwater robot depends on the thrust generated by each bilge pump. The relationship between the power consumption and the thrust of the bilge pump is established using experimental data. The formulated optimal thrust allocation problem is solved using Mincon (Sequential Quadratic Programming) and SA (Simulated Annealing) optimization algorithm. The percentage savings in total power consumption for thruster system using the SA method as compared to Mincon method is 50.6 %.

Underwater robots have been promoted a significant interest in monitoring the marine environment. In some complex situation, robots sometimes need to keep moving fast, sometimes need to keep low speed and low noise. To address this issue, a novel spherical underwater robot (SUR IV) with hybrid propulsion devices including vectored water-jet and propeller thrusters is proposed in this paper. The diversity of the movement modes is also proposed for the different targets as remote or hover and general or silent. To analyze the hydrodynamic characteristics of the hybrid thruster, the computational fluid dynamics simulation is calculated in ANSYS CFX by using the multi-reference frame method. The simulation results show the interaction between the propeller and water-jet thruster. The thrust experiment to evaluate the performance of the improved hybrid thruster is also conducted. The maximum thrust of the hybrid thruster is increased 2.27 times than before. In addition, a noise comparison experiment is conducted to verify the low noise of the water-jet thruster. Finally, the 3 DoF motions which include the surge, heave and yaw for the SUR IV were carried out in the swimming pool. The improvement of the overall robot is assessed by the experimental results.

This research aims to improve the collaboration ability and stability of the Spherical Underwater Robots (SUR III). According to our previous researches in last few years, the SURIII has no control stability module. This paper designed a new torque gyro control and PID control devoted to improve the stability of SUR III. In this new system, we used a gyro sensor and PID control to design a closed-loop control module to perform terrestrial underwater efficiently. Regarding the spherical robot mechanical structure and dynamic model, the robot control module is designed, and set up to complete underwater experiments. In the underwater experiment, the SUR III can stability motion. A certain offset occurs of SUR III under the disturbance of the wind. After the adjustment of the balance control module, the SUR III balance is quickly restored. In addition, it is certainly worth analyzing the underwater motion to evaluate the performance of the robot stability motion.

Underwater target acquisition and identification performed by manipulators having broad application prospects and value in the field of marine development. Conventional manipulators are too heavy to be used for small target objects and unsuitable for shallow sea working. In this paper, a bio-inspired Father–Son Underwater Robot System (FURS) is designed for underwater target object image acquisition and identification. Our spherical underwater robot (SUR), as the father underwater robot of the FURS, has the ability of strong dynamic balance and good maneuverability, can realize approach the target area quickly, and then cruise and surround the target object. A coiling mechanism was installed on SUR for the recycling and release of the son underwater robot. A Salamandra-inspired son underwater robot is used as the manipulator of the FURS, which is connected to the spherical underwater robot by a tether. The son underwater robot has multiple degrees of freedom and realizes both swimming and walking movement modes. The son underwater robot can move to underwater target objects. The vision system is installed to enable the FURS to acquire the image information of the target object with the aid of the camera, and also to identify the target object. Finally, verification experiments are conducted in an indoor water tank and outdoor swimming pool conditions to verify the effectiveness of the proposed in this paper.

To improve the adaptability of the spherical mobile robot in unknown environment, this paper proposed the behavior-based fuzzy control method, and integrated fuzzy obstacle avoidance performance into this method. Firstly, the sensors were arranged according to the motion model of the spherical mobile robot, and which improved the flexibility and autonomy of the spherical mobile robot in unstructured environment. In the process of motion, the spherical mobile robot use multi-sensor, which is used to collect the obstacles and the target position information in the environment, to complete the path planning. Then, the MobotSim simulation platform was used to design the behavior-based control experiments for the spherical mobile robot, including wall-following, through narrow road, obstacle avoidance and trending target experiments.etc. The simulation results verified the validity and reliability of the fuzzy control system. Finally, the path planning experiments in the real environment was completed, which controlled the spherical mobile robot behavior by fuzzy controller and priority decisions, including obstacle avoidance, wall-following, cruising, tending to target and unlocking the deadlock behaviors, and so on, and modified the pose of the robot based on the angle of real-time feedback information to avoid obstacles precisely. The experimental results showed that the spherical mobile robot could complete control method based on behavior, further verified the effectiveness and practicability of the fuzzy control system.

In the navigation of underwater robots, large ocean current disturbance often causes significant tracking errors. To better resist ocean current disturbance, the hydrodynamic characteristics of the spherical underwater robot are studied, and a model predictive control strategy based on adaptive model parameters is proposed, according to these characteristics. Firstly, the hydrodynamic characteristics of the robot under static water and constant flow disturbance were obtained and analyzed by the computational fluid dynamics method. Then, the dynamic models of the robot under different disturbances could be calculated from the data obtained, based on the least square method. Finally, an adaptive model predictive control (AMPC) strategy, with an ocean current observer, was designed, based on the dynamic models. When the current disturbance velocity was twice the robot velocity, the proposed strategy reduced the tracking error by 39% and 42% in X and Y directions, respectively. In addition, the hydrodynamic characteristics were verified by experiments.

Recently, researchers from throughout the world have concentrated their efforts on amphibious robots inspired by amphibians. Because of their exceptional adaptability, amphibian robots may be used in a wide range of applications, including scientific, commercial, and military ventures. With such advantages, the design of a spherical amphibian underwater robot should consider the constraint that all components must be kept within the sphere, and that reducing the size would lessen the buoyancy force resting on it. The purpose of this dissertation is to propose a novel structural design for a spherical amphibian underwater robot with aim to secure all of the components by placing them within the sphere and to ensure that the proposed design can travel on land and underwater without changing its structure while consume less energy. The prototyping process was done using rapid prototyping machine (RPM) after digital design created in Fusion 360 is finalize. The proposed prototype weighs 4.728 kg with a diameter of 35 cm. The prototype is appropriate for system identification and modelling, as well as control system testing platform.

The path of the mobile robot is a multi-objective optimization problem. The traditional ant colony algorithm is introduced into the path planning of the mobile robot. Due to the complexity of the robot path, the large search space and the low efficiency, it is easy to fall into the local optimum and even deadlock and other defeats. In order to enhance the efficiency and accuracy of path planning, a path planning algorithm of mobile robot based on ant colony algorithm is proposed. The path planning of mobile robot is simulated under grid environment. The experimental results show that the improved algorithm can improve the efficiency of path planning for mobile robot, safely avoid obstacles and find all the optimal solutions in the shortest time.

To achieve real-time obstacle avoidance for underwater robots, the artificial potential field method can be selected as the obstacle avoidance path planning algorithm. However, this method applies a large attractive force to the underwater robot when it is far from the target point, causing it to collide with obstacles. Additionally, when the underwater robot just enters the repulsion influence zone, the repulsion force that it experiences undergoes an abrupt change, resulting in a non-smooth obstacle avoidance path. Furthermore, developing the obstacle avoidance function based on software platforms such as MATLAB has a long algorithm verification cycle, and it is difficult to transfer the algorithm model to practical scenarios. Therefore, this paper proposes an underwater robot obstacle avoidance method based on ROS. Firstly, a dynamic adjustment factor is introduced into the potential field function of the artificial potential field method to redefine the obstacle influence zone, and an improved artificial potential field method is designed as the obstacle avoidance path planning algorithm for underwater robots. The experiment is conducted on the ROS simulation platform, and the results show that the improved algorithm can solve the two problems existing in the artificial potential field method. Secondly, nodes required for underwater robot obstacle avoidance are established based on the ROS operating system, and the improved artificial potential field method is integrated into the obstacle avoidance path planning node. Finally, the obstacle avoidance experiment of the Bluerov2 underwater robot is conducted in a pool, and the experimental results demonstrate that the proposed method can achieve real-time obstacle avoidance for underwater robots.

This paper describes the development of the second-generation Spherical Underwater Robot (SUR-II). The new SUR-II has an improved propulsion system structure, resulting in better performance compared with the original design. This paper focuses on the characteristics of the water-jet thruster and the spherical hull of the SUR-II. To analyse its hydrodynamic characteristics, the main hydrodynamic parameters of the SUR-II were estimated based on two reasonable assumptions and a reasonable dynamic equation was proposed to describe the relationship between force and velocity. Drag coefficients were calculated separately for vertical and horizontal motions due to the fin on the robot's equator and the holes in the robot's hull. The holes had a particularly adverse effect on the horizontal drag coefficient. A hydrodynamic analysis using computational fluid dynamics was then carried out to verify the estimated parameters. The velocity vectors, pressure contours and drag coefficient for each state of motion were obtained. Finally, the propulsive force was determined experimentally to verify the theoretical calculations and simulation results.

Characteristic evaluation via multi-sensor information fusion strategy for spherical underwater robots

Spherical robots are generally comprised of a spherical shell and an internal actuation unit. These robots have a variety of applications ranging from search and rescue to agriculture. Although one of the main advantages of spherical robots is their capability to operate on uneven surfaces, energy analysis and path planning of such systems have been studied only for flat terrains. This work introduces a novel approach to evaluate the dynamic equations, energy consumption, and separation analysis of these robots rolling on uneven terrains. The presented dynamics modeling, separation analysis, and energy analysis allow us to implement path planning algorithms to find an optimal path. One of the advantages of this work is that these algorithms can be used when either the analytical or the empirical information about the terrain is available.