Switched Modeling and Task–Priority Motion Planning of Wheeled Mobile Robots Subject to Slipping

This study is devoted to the modelling and control of Wheeled Mobile Robots moving with longitudinal and lateral slips of all wheels. Due to wheel slippage we have to deal with systems with changing dynamics. Wheeled Mobile Robots can be thus modeled as switched systems with both autonomous switches (due to wheel slippage) and smooth controls (due to control algorithm). It is assumed that the slipping is counteracted by the slip reaction forces acting at contact points of the wheels with the ground. A model of these reaction forces, borrowed from the theory of automotive systems, has been adopted and included into the Lagrangian dynamic equations of the robot. A framework for designing motion planning schemes devoid of chattering effects for systems with changing dynamics is presented. A task–priority motion planning problem for wheeled mobile robots subject to slipping is addressed and solved by means of Jacobian motion planning algorithm based on the Endogenous Configuration Space Approach. Performance of the algorithm is presented in simulations of the Pioneer 2DX mobile platform. The robot dynamics equations are derived and 4 variants of motion are distinguished. The motion planning problem is composed of two sub-tasks: robot has to reach a desired point in the task space (proper motion planning) and the motion should minimize either the control energy expendinture or the wheel slippage. Performance of the motion planning algorithm is illustrated by a sort of the parking maneuver problem.     

Obstacle avoidance of snake robot by switching control constraint

In this paper, we propose an obstacle avoidance method for autonomous locomotion control of a snake robot. The snake robot consists of rigid links, active joints and passive wheels, and can move only by varying its shape. The pass planning for the obstacle avoidance is a complicated problem because the snake robot has many states, control inputs and the under-actuated property. In our proposed method, the snake motion is restricted to a periodic undulate curve (called a serpenoid curve) by an additional control constraint and the undulate curve is tuned by switching the control constraint in order that the snake robot avoids the obstacle. Therefore, the path planning is simplified and the snake robot will achieve the obstacle avoidance with an efficient path. In this paper, we denote the details of our method and investigate the effectiveness of our strategy by numerical simulations.     

An approach to analyzing biped locomotion dynamics and designing robot locomotion controls

An approach to analyzing biped locomotion problems is presented. This approach applies the principles of Lagrangian dynamics to derive the equations of motion of locomotion gaits, state-variable techniques to analyze locomotion dynamics, and multivariable feedback to design locomotion controls. A robot model which has no knee joints or feet and is constrained to motion in the sagittal plane is chosen as a sufficiently simple model of a biped to illustrate the approach. A goal of the analysis is the design of a locomotion control for the robot which produces a walking gait having a velocity and stride length similar to those of a human walking gait. The principle feature of the approach is a much deeper understanding of the dynamics of biped locomotion than previous approaches have provided.     

机器人运动规划方法的研究

针对路径规划以及碰撞检测这一研究的重点问题,提出了G-空间法、人工势力场法、遗传算法等。序列规划问题一般转化为旅行商问题来求解。在综合现有序列规划和路径规划方法的基础上,提出两种机器人运动规划算法：基于任意路径的运动规划算法和基于直线路径的运动规划算法,思路简单,能对各种机器人工程任务进行运动规划。     

Motion planning algorithms of an omni-directional mobile robot with active caster wheels

This work deals with motion planning algorithms of an omni-directional mobile robot with active caster wheels. A typical problem occurred in the motion control of such omni-directional mobile robot, which has been identified through experimental experiences, is skidding of the mobile wheel. It sometimes results in uncertain rotation of the steering wheel. To cope with this problem, a motion planning algorithm which resolves the skidding problem and uncertain motions of the steering wheel is mainly investigated. For navigation of the mobile robot, the posture of the omni-directional mobile robot is initially calculated using the odometry information. Then, the accuracy of the mobile robot’s odometry is measured through comparison of the odometry information and the external sensor measurement. Finally, for successful navigation of the mobile robot, a motion planning algorithm that employs kinematic redundancy resolution method is proposed. Through simulations and experimentation, the feasibility of proposed algorithms was verified.     

Upper-body haptic system for snake robot teleoperation in pipelines

Snake robots have shown a great potential for operations in confined workplaces that are less accessible or dangerous to human workers, such as the in-pipe inspection. However, the snake robot teleoperation remains a nontrivial task due to the unique locomotion mechanism (e.g., helical motion) and the constraints of the workplaces including the low visibility and indistinguishable features. Most snake robot feedback systems are based on the live camera view only. It is hard for the human operator to develop a correct spatial understanding of the remote workplace, leading to problems such as disorientation and motion sickness in snake robot teleoperation. This study designs and evaluates an innovative haptic assistant system for snake robot teleoperation in the in-pipe inspection. An upper-body haptic suit with 40 vibrators on both the front and back sides of the human operator was developed to generate haptic feedback corresponding to the bottom and up sides of the snake robot, transferring the egocentric sensation of the snake robot to the human operator. A human-subject experiment (n = 31) was performed to evaluate the efficacy of the developed system. The results indicate that the proposed haptic assistant system outperformed other feedback systems in terms of both task performance and subjective workload and motion sickness evaluations. It inspires new control and feedback designs for the future snake robot in industrial operations.     

机械臂最优运动规划问题的混合粒子群算法

多关节机械臂路径规划是一个高度受限的非线性优化问题,很难找到单一的优化解.提出一种基于单纯形算法和粒子群算法的混合算法,以解决机械臂的路径规划问题.仿真试验表明,相较于常规的A*算法,该混合算法具有更高的求解精度.     

Snake terrestrial locomotion synthesis in 3D virtual environments

We present a method for a 3D snake model construction and terrestrial snake locomotion synthesis in 3D virtual environments using image sequences. The snake skeleton is extracted and partitioned into equal segments using a new iterative algorithm for solving the equipartition problem. This method is applied to 3D model construction and at the motion analysis stage. Concerning the snake motion, the snake orientation is controlled by a path planning method. An animation synthesis algorithm, based on a physical motion model and tracking data from image sequences, describes the snake’s velocity and skeleton shape transitions. Moreover, the proposed motion planning algorithm allows a large number of skeleton shapes, providing a general method for aperiodic motion sequences synthesis in any motion graph. Finally, the snake locomotion is adapted to the 3D local ground, while its behavior can be easily controlled by the model parameters yielding the appropriate realistic animations.     

The VFO-Driven Motion Planning and Feedback Control in Polygonal Worlds for a Unicycle with Bounded Curvature of Motion

Integrated motion planning and control for the purposes of maneuvering mobile robots under state- and input constraints is a problem of vital practical importance in applications of mobile robots such as autonomous transportation. Those constraints arise naturally in practice due to specifics of robot mechanical construction and the presence of obstacles in motion environment. In contrast to approaches focusing on feedback control design under the assumption of given reference motion or motion planning with neglection of subsequent feedback motion execution, we adopt a controller-driven motion planning paradigm, which has recently gained attention of many researchers. It postulates design of motion planning algorithms dedicated to specific feedback control policies, which compute a sequence of feedback control subtasks instead of classically planned open-loop controls or parametric paths. In this spirit, we propose a motion planning algorithm driven by the VFO (Vector Field Orientation) control law for the waypoint-following task. Presented analysis of the VFO control law reveals its beneficial properties, which are subsequently utilized to solve a generally nonlinear and non-convex optimal motion planning problem by formulating it as a mixed-integer linear program (MILP). The solution proposed in this paper yields a waypoint sequence, which is designed for execution by application of the VFO control law to drive a robot to a prescribed final configuration under an input constraint imposed by bounded curvature of robot motion and state constraints resulting from a convex decomposition of task space. Satisfaction of these constraints is guaranteed analytically and exactly, i.e., without utilization of numerical approximations. Moreover, for a given discrete set of possible waypoint orientations, the proposed algorithm computes plans optimal w.r.t. given cost functional, which can be any convex linear combination of quantities such as robot path length, curvature of robot motion, distance to imposed state constraints, etc. Furthermore, the planning algorithm exploits the possibility of both forward or backward movement of the robot to allow maneuvering in demanding environments. Generated waypoint sequences are a compact representation of a motion plan, which can be immediately executed with the VFO controller without any additional post-processing. Validity of the proposed approach has been confirmed by simulation studies and experimental motion execution with a laboratory-scale mobile robot.     

An integrated robust probing motion planning and control scheme: A tube-based MPC approach

‘This paper introduces the integration of a probing scheme into a robust MPC-based robot motion planning and control algorithm. The proposed solution tackles the output-feedback tube-based MPC problem using the partially-closed loop strategy to incorporate future measurements in a computationally efficient manner. This combination will provide not only a robust controller but also avoids overly conservative planning which is a drawback of the original implementation of the output-feedback tube-based MPC. The proposed solution is composed of two controllers: (i) a nominal MPC controller with probing feature to plan a globally convergent trajectory in conjunction with active localization, and (ii) an ancillary MPC controller to stabilize the robot motion around the planned trajectory. The performance and real-time implementation of the proposed planning and control algorithms have been verified through both extensive numerical simulations and experiments with a mobile robot.     

仿蛇变体机器人运动机理研究

本文设计了一种蛇形机器人，分析了蛇形机器人的结构，详细讨论了蛇形机器人的运 动机理和几何结构关系，并推导出蛇形机器人的控制算法和相应的控制程序，蛇形机器人在 程序控制下能够向前、向后运动，在一定程度上实现了蛇的运动．     

Constrained motion planning of nonholonomic systems

This paper addresses the constrained motion planning problem for nonholonomic systems represented by driftless control systems with output. The problem consists in defining a control function driving the system output to a desirable point at a given time instant, whereas state and control variables remain over the control horizon within prescribed bounds. The state and control constraints are handled by extending the control system with a pair of state equations driven by the violation of constraints, and adding regularizing perturbations. For the regularized system a Jacobian motion planning algorithm is designed, called imbalanced. Solutions of example constrained motion planning problems for the rolling ball illustrate the theoretical concepts.     

Transputer arrays for the on-line computation of robot jacobians

On-line computation of forward and inverse Jacobian matrices is essential in robot manipulator controllers, where high-speed robot motion is required. The complexity of Jacobian calculation is such that the computational burden is large, and parallel processing is necessary if on-line computation is to be achieved. Various algorithms and parallel-processing networks suitable for this are considered. All algorithms have been implemented on transputer networks and computation times measured. The paper emphasises the importance of including communication overheads in comparisons of the computational efficiency of alternative algorithms and processor networks. Theoretical processing times based on computer cycle times and arithmetic operation counts are shown to be a false basis for comparison. Whilst considering the specific case of computation of Jacobian matrices for a robot manipulator, the paper provides a useful example of the considerations and constraints involved in distributing any algorithm across a multi-processor network.     

Motion planning algorithms for molecular simulations: A survey

Motion planning is a fundamental problem in robotics that has motivated research since more than three decades ago. A large variety of algorithms have been proposed to compute feasible motions of multi-body systems in constrained workspaces. In recent years, some of these algorithms have surpassed the frontiers of robotics, finding applications in other domains such as industrial manufacturing, computer animation and computational structural biology. This paper concerns the latter domain, providing a survey on motion planning algorithms applied to molecular modeling and simulation. Both the algorithmic and application sides are discussed, as well as the different issues to be taken into consideration when extending robot motion planning algorithms to deal with molecules. From an algorithmic perspective, the paper gives a general overview of the different extensions to sampling-based motion planners. From the point of view of applications, the survey deals with problems involving protein folding and conformational transitions, as well as protein–ligand interactions.     

An Optimal Control-Based Formulation to Determine Natural Locomotor Paths for Humanoid Robots

In this paper we explore the underlying principles of natural locomotion path generation of human beings. The knowledge of these principles is useful to implement biologically inspired path planning algorithms on a humanoid robot. By 'locomotion path' we denote the motion of the robot as a whole in the plane. The key to our approach is to formulate the path planning problem as an optimal control problem. We propose a single dynamic model valid for all situations, which includes both non-holonomic and holonomic modes of locomotion, as well as an appropriately designed unified objective function. The choice between holonomic and non-holonomic behavior is not accomplished by a switching model, but it appears in a smooth way, along with the optimal path, as a result of the optimization by efficient numerical techniques. The proposed model and objective function are successfully tested in six different locomotion scenarios. The resulting paths are implemented on the HRP-2 robot in the simulation environment OpenHRP as well as in the experiment on the real robot.     

NSGA-Ⅱ在蛇形机器人中的优化与控制

研究蛇形机器人蜿蜒运动步态的优化与控制问题。结合摩擦力模型,并分析蛇形机器人运动步态模型,根据基于闭环反馈的控制系统结构运用PID控制器对其步态进行跟踪控制,在此基础上采用基于非支配排序遗传算法(NSGA-Ⅱ)对步态进行优化,该优化方法实现对闭环反馈跟踪控制系统的参数优化。仿真结果表明,NSGA-Ⅱ算法能达到变量优化目的,在功率和速度之间寻找最优值,对于解决蛇形机器人运动步态多目标优化问题是可行有效的。     

空间机器人连续运动轨迹控制建模和仿真研究

基于地面机器人常用的D-H 建模方法和空间机器人（SR）满足的动量守恒和角动量守恒原理,提出 了SR 连续运动轨迹控制建模算法．首先基于地面机器人雅可比矩阵的思想和D-H 法,建立了适用于空间机器人 的运动学模型;其次研究了空间机器人的广义雅可比矩阵计算及其连续运动轨迹控制的有效算法;最后通过计算 机仿真验证了所提出算法的有效性．本文基于D-H 方法的SR 概念模型和运动学模型可推广到包含旋转关节和平 移关节的树型结构链杆的任何SR．     

Dynamic path planning for a mobile automaton with limited information on the environment

The problem of path planning is studied for the case of a mobile robot moving in an environment filled with obstacles whose shape and positions are not known. Under the accepted model, the automaton knows its own and the target coordinates, and has a "sensory" feedback which provides it with local information on its immediate surroundings. Ibis information is shown to be sufficient to guarantee reaching a global objective (the target), while generating reasonable (if not optimal) paths. A lower bound on the length of paths generated by any algorithm operating with uncertainty is formulated, and two nonheuristic path planning algorithms are described. In the algorithms, motion planning is done continuously (dynamically), based on the automaton's current position and on its feedback. The effect of additional sources of information (e.g., from a vision sensor) on the outlined approach is discussed.     

基于改进蚁群算法的四足机器人步态规划

四足机器人关节众多、运动方式复杂,步态规划是四足机器人运动控制的基础。传统的算法多基于仿生原理,缺乏广泛适应性。 在建立运动学方程的基础上,提出了一种基于改进蚁群算法的步态规划算法。该算法利用了四足机器人4条腿运动的线性无关性,将步态规划问题转换为在四维空间里求取最长路径问题。仿真结果表明,该算法得出了满足约束条件的所有步态,最后通过机器人样机检验,验证了该算法求取结果的有效性和合理性。     

基于ROS的蛇形机器人基本仿生运动与自主爬台阶控制

设计了一种带正交关节和主动轮组合的蛇形机器人。该机器人不仅能够实现基本的蜿蜒运动、纵向行波运动、横向翻滚运动和横向行波运动,且针对台阶式障碍物提出了一种自主爬越台阶的控制策略。机器人通过激光测距传感器与头部关节的仰角得到台阶高度,抬起相应高度的关节将头关节搭在台阶上,控制主动轮的推进速度与关节抬起的角速度相结合的方式达到上台阶的目的,并且在运动过程中将头部俯仰关节舵机的负载反馈作为判别下台阶的条件。基于ROS （robot operating system）构建了蛇形机器人仿真模型,并通过仿真与实验验证了机器人的基本运动控制和自主爬台阶控制策略的有效性。