Experimental study on fine motion control of underwater robots

This paper considers thruster dead zones and saturation limits, which are nonlinear elements that complicate fine motion control of underwater robots. If the vehicle is configured with redundant thrusters, the respective dead zones and their surrounding nonlinear regions could be avoided by implementing a null motion solution for the command input of the vehicle. This solution is derived from the vehicle's geometry and is realized before the application of the motion control algorithm. The result is an improvement in system performance exclusive of the implemented controller type. The approach is illustrated through simulation and experiment with an underwater robot, ODIN.     

水下机器人定位算法

水下机器人的定位信息一般应包括位置信息和航向信息。选用超声波传感器测距,再作圆弧求交点的方法可获取位置信息,给出2种计算位置的算法;水下环境复杂,机器人的航向信息难以获取,建立拟合机器人的历史位置信息的曲线,进而对曲线进行求导来近似代替机器人航向的航向估计模型。水下实验验证了定位算法的可行性及可靠性,位置定位绝对误差小于20 cm,航向定位绝对误差大都在10°以内,满足定位要求。并分析定位误差来源,给出航向算法的修正模型。     

Multi-objective migrating bird optimization algorithm for cost-oriented assembly line balancing problem with collaborative robots

Neural Computing and Applications - Industries are increasingly looking for opportunities at utilizing collaborative robots in assembly lines to perform the tasks independently or assist the human...     

Optimal motion planning for parallel robots via convex optimization and receding horizon

In this paper, the problem of motion planning for parallel robots in the presence of static and dynamic obstacles has been investigated. The proposed algorithm can be regarded as a synergy of convex optimization with discrete optimization and receding horizon. This algorithm has several advantages, including absence of trapping in local optimums and a high computational speed. This problem has been fully analyzed for two three-DOF parallel robots, ie 3s-RPR parallel mechanism and the so-called Tripteron, while the shortest path is selected as the objective function. It should be noted that the first case study is a parallel mechanism with complex singularity loci expression from a convex optimization problem standpoint, while the second case is a parallel manipulator for which each limb has two links, an issue which increases the complexity of the optimization problem. Since some of the constraints are non-convex, two approaches are introduced in order to convexify them: (1) A McCormick-based relaxation merged with a branch-and-prune algorithm to prevent it from becoming too loose and (2) a first-order approximation which linearizes the non-convex quadratic constraints. The computational time for the approaches presented in this paper is considerably low, which will pave the way for online applications.     

Collision-free and smooth joint motion planning for six-axis industrial robots by redundancy optimization

Planning collision-free and smooth joint motion is crucial in robotic applications, such as welding, milling, and laser cutting. Kinematic redundancy exists when a six-axis industrial robot performs five-dimensional tasks, and there are infinite joint configurations for a six-axis industrial robot to realize a cutter location data of the tool path. The robot joint motion can be optimized by taking advantage of the kinematic redundancy, and the collision-free joint motion with minimum joint movement is determined as the optimal. However, most existing redundancy optimization methods do not fully exploit the redundancy of the six-axis industrial robots when they conduct five-dimensional tasks. In this paper, we present an optimization method to solve the problem of inverse kinematics for a six-axis industrial robot to synthesize the joint motion that follows a given tool path, while achieving smoothness and collision-free manipulation. B-spline is applied for the joint configuration interpolation, and the sum of the squares of the first, second, and third derivatives of the B-spline curves are adopted as the smoothness indicators. Besides, the oriented bounding boxes are adopted to simplify the shape of the robot joints, robot links, spindle unit, and fixtures to facilitate collision detections. Dijkstra's shortest path technique and Differential Evolution algorithm are combined to find the optimal joint motion efficiently and avoid getting into a local optimal solution. The proposed algorithm is validated by simulations on two six-axis industrial robots conducting five-axis flank milling tasks respectively.     

浆液下机器人定位功能实现

设计液下搅拌机器人的定位系统,选用多传感器来获取定位信息。用单片机(下位机)测得各个传感器信息,通过RS—485总线把信息传给工控机(上位机),工控机对信息进行融合,实时(本系统可达1 s)获得机器人的位置及航向信息。实验验证定位系统可行性,并对测距误差进行了分析,修正后定位误差在10 cm以内,满足对机器人的定位要求。     

Toward efficient path-planning for articulated robots

Real-time issues are becoming more and more important in robot programming. When a 6-dof manipulator is used, planning obstacle-avoiding paths is a time-consuming activity, usually done in simulation. We present the geometric models and the reasoning techniques we have implemented while realizing a gross motion planner for a manipulator with six revolute joints. First, construction of a problem-oriented representation of the robot working space is explained. Then, the actual trajectory research carried out in our C-space representation is described. The whole C-space is not calculated; instead, a sequential strategy is used to determine the C-space only for the first two links. Our approximation of the obstacles, which occupy fixed and known positions, greatly speeds the computation, allowing us to reduce the problem to planar geometric reasoning. The work is not limited to theoretical studies or simulations; experiments have been run very thoroughly, with various tests, on a PUMA robot to assess the real efficiency and usability of our software. The method applies to robots in a fixed and known environment. © 3995 John Wiley & Sons, Inc.     

Formation control of underactuated bio-inspired snake robots

This paper considers formation control of snake robots. In particular, based on a simplified locomotion model, and using the method of virtual holonomic constraints, we control the body shape of the robot to a desired gait pattern defined by some pre-specified constraint functions. These functions are dynamic in that they depend on the state variables of two compensators which are used to control the orientation and planar position of the robot, making this a dynamic maneuvering control strategy. Furthermore, using a formation control strategy we make the multi-agent system converge to and keep a desired geometric formation, and enforce the formation follow a desired straight line path with a given speed profile. Specifically, we use the proposed maneuvering controller to solve the formation control problem for a group of snake robots by synchronizing the commanded velocities of the robots. Simulation results are presented which illustrate the successful performance of the theoretical approach.     

一种水下群机器人路径规划算法的形式化研究

为了增强基于遗传算法的水下群机器人路径规划算法正确性的说服力,使用定理证明对其进行形式化研究,给出算法在定理证明器HOL4中的形式化模型。基于算法形式化的一般步骤,首先对算法的设计进行了详细的分析,指出算法设计的核心步骤与建模难点。在此基础上建立了总体形式化建模框架,然后对其进行化简,得到种群初始化、选择、交叉三个核心模块。接着给出模型中要用到的基本数据类型的形式化描述,并分别对三个模块进行形式化描述,最终得到算法的形式化模型。通过证明与模型相关的97条性质,说明了模型的合理性及有效性,在此模型的基础上,可以完成对算法的形式化验证,同时还能拓展HOL4的应用范围。     

Multi-objective ordinal optimization for simulation optimization problems

Ordinal optimization (OO) has been successfully applied to accelerate the simulation optimization process with single objective by quickly narrowing down the search space. In this paper, we extend the OO techniques to address multi-objective simulation optimization problems by using the concept of Pareto optimality. We call this technique the multi-objective OO (MOO). To define the good enough set and the selected set, we introduce two performance indices based on the non-dominance relationship among the designs. Then we derive several lower bounds for the alignment probability under various scenarios by using a Bayesian approach. Numerical experiments show that the lower bounds of the alignment probability are valid when they are used to estimate the size of the selected set as well as the expected alignment level. Though the lower bounds are conservative, they have great practical value in terms of narrowing down the search space.     

Coordinated motion planning for two independent robots

We present anO(n ²) algorithm for planning a coordinated collision-free motion of two independent robot systems of certain kinds, each having two degrees of freedom, which move in the plane amidst polygonal obstacles having a total ofn corners. We exemplify our technique in the case of two planar Stanford arms, but also discuss the case of two discs or convex translating objects. The algorithm improves previous algorithms for this kind of problems, and can be extended to a fairly simple general technique for obtaining efficient coordinated motion planning algorithms.     

High-level motion planning for CPG-driven modular robots

Modular robots may become candidates for search and rescue operations or even for future space missions, as they can change their structure to adapt to terrain conditions and to better fulfill a given task. A core problem in such missions is the ability to visit distant places in rough terrain. Traditionally, the motion of modular robots is modeled using locomotion generators that can provide various gaits, e.g. crawling or walking. However, pure locomotion generation cannot ensure that desired places in a complex environment with obstacles will in fact be reached. These cases require several locomotion generators providing motion primitives that are switched using a planning process that takes the obstacles into account. In this paper, we present a novel motion planning method for modular robots equipped with elementary motion primitives. The utilization of primitives significantly reduces the complexity of the motion planning which enables plans to be created for robots of arbitrary shapes. The primitives used here do not need to cope with environmental changes, which can therefore be realized using simple locomotion generators that are scalable, i.e., the primitives can provide motion for robots with many modules. As the motion primitives are realized using locomotion generators, no reconfiguration is required and the proposed approach can thus be used even for modular robots without self-reconfiguration capabilities. The performance of the proposed algorithm has been experimentally verified in various environments, in physical simulations and also in hardware experiments.     

Temporal logic motion planning for dynamic robots

In this paper, we address the temporal logic motion planning problem for mobile robots that are modeled by second order dynamics. Temporal logic specifications can capture the usual control specifications such as reachability and invariance as well as more complex specifications like sequencing and obstacle avoidance. Our approach consists of three basic steps. First, we design a control law that enables the dynamic model to track a simpler kinematic model with a globally bounded error. Second, we built a robust temporal logic specification that takes into account the tracking errors of the first step. Finally, we solve the new robust temporal logic path planning problem for the kinematic model using automata theory and simple local vector fields. The resulting continuous time trajectory is provably guaranteed to satisfy the initial user specification.     

Kinematic motion model for jumping scout robots

/sup T/he University of Minnesota's Scout is a small cylindrical robot capable of rolling and jumping. Models describing the robot's motion are developed. These models can be employed for motion prediction and simulation. The results suggest that the determining factor of the Scout's behavior is the length of the winch cable.     

A virtual environment-based system for the navigation of underwater robots

Efficient teleoperation of underwater robot requires clear 3D visual information of the robot's spatial location and its surrounding environment. However, the performance of existing telepresence systems is far from satisfactory. In this paper, we present our virtual telepresence system for assisting tele-operation of an underwater robot. This virtual environment-based telepresence system transforms robot sensor data into 3D synthetic visual information of the workplace based on its geometrical model. It provides the operators with a full perception of the robot's spatial location. In addition, we propose a robot safety domain to overcome the robot's location offset in the virtual environment caused by its sensor errors. The software design of the system and how a safety domain can be used to overcome robot location offset in virtual environment will be examined. Experimental tests and its result analysis will also be presented in this paper.     

Real-time method for tip following navigation of continuum snake arm robots

This paper presents a novel technique for the navigation of a snake arm robot, for real-time inspections in complex and constrained environments. These kinds of manipulators rely on redundancy, making the inverse kinematics very difficult. Therefore, a tip following method is proposed using the sequential quadratic programming optimization approach to navigate the robot. This optimization is used to minimize a set of changes to the arrangement of the snake arm that lets the algorithm follow the desired trajectory with minimal error. The information of the Snake Arm pose is used to limit deviations from the path taken. Therefore, the main objective is to find an efficient objective function that allows uninterrupted movements in real-time. The method proposed is validated through an extensive set of simulations of common arrangements and poses for the snake arm robot. For a 24 DoF robot, the average computation time is 0.4 s, achieving a speed of 4.5 mm/s, with deviation of no more than 25 mm from the ideal path.     

Multi-objective efficient global optimization of expensive simulation-based problem in presence of simulation failures

The multi-objective efficient global optimization (MOEGO), an extension of the single-objective efficient global optimization algorithm with the intention to handle multiple objectives, is one of the most frequently studied surrogate model-based optimization algorithms. However, the evaluation of the infill point obtained in each MOEGO update iteration using simulation tool may fail. Such evaluation failures are critical to the sequential MOEGO method as it leads to a premature halt of the optimization process due to the impossibility of updating the Kriging models approximating objectives. In this paper, a novel strategy to prevent the premature halt of the sequential MOEGO method is proposed. The key point is to introduce an additional Kriging model to predict the success possibility of the simulation at an unvisited point. Multi-objective expected improvement-based criteria incorporating the success possibility of the simulation are proposed. Experiments are performed on a set of six analytic problems, five low-fidelity airfoil shape optimization problems, and a high-fidelity axial flow compressor tandem cascade optimization problem. Results suggest that the proposed MOEGO-Kriging method is the only method that consistently performs well on analytic and practical problems. The methods using the least-square support vector machine (LSSVM) or weighted LSSVM as the predictor of success possibility perform competitively or worse compared with MOEGO-Kriging. The penalty-based method, assigning high objective values to the failed evaluations in minimization problem, yields the worst performance.