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.     

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。     

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.     

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.     

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.     

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.     

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.     

Emergent synthesis of motion patterns for locomotion robots

Emergence of stable gaits in locomotion robots is studied in this paper. A classifier system, implementing an instance-based reinforcement-learning scheme, is used for the sensory-motor control of an eight-legged mobile robot and for the synthesis of the robot gaits. The robot does not have a priori knowledge of the environment and its own internal model. It is only assumed that the robot can acquire stable gaits by learning how to reach a goal area. During the learning process the control system is self-organized by reinforcement signals. Reaching the goal area defines a global reward. Forward motion gets a local reward, while stepping back and falling down get a local punishment. As learning progresses, the number of the action rules in the classifier systems is stabilized to a certain level, corresponding to the acquired gait patterns. Feasibility of the proposed self-organized system is tested under simulation and experiment. A minimal simulation model that does not require sophisticated computational schemes is constructed and used in simulations. The simulation data, evolved on the minimal model of the robot, is downloaded to the control system of the real robot. Overall, of 10 simulation data seven are successful in running the real robot.     

Multidisciplinary optimization design of a new underwater vehicle with highly efficient gradient calculation

Structural and Multidisciplinary Optimization - In order to reduce the cost of oceanographic exploration, a new underwater vehicle is designed to sail the required distance with the lowest energy...     

Multi-objective optimization using teaching-learning-based optimization algorithm

Two major goals in multi-objective optimization are to obtain a set of nondominated solutions as closely as possible to the true Pareto front (PF) and maintain a well-distributed solution set along the Pareto front. In this paper, we propose a teaching-learning-based optimization (TLBO) algorithm for multi-objective optimization problems (MOPs). In our algorithm, we adopt the nondominated sorting concept and the mechanism of crowding distance computation. The teacher of the learners is selected from among current nondominated solutions with the highest crowding distance values and the centroid of the nondominated solutions from current archive is selected as the Mean of the learners. The performance of proposed algorithm is investigated on a set of some benchmark problems and real life application problems and the results show that the proposed algorithm is a challenging method for multi-objective algorithms.     

Adaptive controller design for underwater snake robot with unmatched uncertainties

Because of hydrodynamic model error of the present dynamic model, there is a challenge in controller design for the underwater snake-like robot. To tackle this challenge, this paper proposes an adaptive control schemes based on dynamic model for a planar, underwater snake-like robot with model error and time-varying noise. The adaptive control schemes aim to achieve the adaptive control of joint angles tracking and the direction of locomotion control. First, through approximation and reducibility using Taylor expansion method, a simplified dynamics model of a planar amphibious snake-like robot is derived. Then, the L1 adaptive controller based on piecewise constant adaptive law is applied on the simplified planar, underwater snake-like robot, which can deal with both matched and unmatched nonlinear uncertainties. Finally, to control the direction of locomotion, an auxiliary bias signal is used as the control input to regulate the locomotion direction. Simulation results show that this L1 adaptive controller is valid to deal with different uncertainties and achieve the joint angles tracking and fast adaptive at the same time. The modified L1 adaptive controller, in which the auxiliary bias item is added, has the ability to change the direction of locomotion, that is, the orientation angle is periodic with arbitrarily given constant on average.