Nonholonomic Path Planning Research Articles

Path Planning for Chainable Non-holonomic System Based on Iterative Learning Control

Non-holonomic path planning is to solve the two point boundary value problem under constraints. Since it is offline and open-loop, the path planning cannot compensate for the disturbances and eliminate the errors. To solve the problems, this paper puts forward an iterative learning control algorithm that adjusts the control parameters of the path planner online through the multiple iterative computations of the target configuration error equation, under the initial configuration error and model error, and thus enhancing the accuracy of non-holonomic system path planning. Then, a simulation experiment on path planning was carried out for a chainable three-joint, non-holonomic manipulator. The results show that the iterative learning controller can eliminate the interference of initial configuration error and model error, such that each joint can move to the target configuration.

Path Planning for a Space-Based Manipulator System Based on Quantum Genetic Algorithm

In this study, by considering a space-based, n-joint manipulator system as research object, a kinematic and a dynamic model are constructed and the system’s nonholonomic property is discussed. In light of the nonholonomic property unique to space-based systems, a path planning method is introduced to ensure that when an end-effector moves to the desired position, a floating base achieves the expected pose. The trajectories of the joints are first parameterized using sinusoidal polynomial functions, and cost functions are defined by the pose deviation of the base and the positional error of the end-effector. At this stage, the path planning problem is converted into a target optimization problem, where the target is a function of the joints. We then adopt a quantum genetic algorithm (QGA) to solve this objective optimization problem to attain the optimized trajectories of the joints and then execute nonholonomic path planning. To test the proposed method, we carried out a simulation on a six-degree-of-freedom (DOF) space-based manipulator system (SBMS). The results showed that, compared to traditional genetic optimization algorithms, the QGA converges more rapidly and has a more accurate output.

Cartesian Non-holonomic Path Planning of Space Robot Based on Quantum-behaved Particle Swarm Optimization Algorithm

Based on the non-holonomic redundancy behavior of free-floating space robot system,a path planning approach is proposed to realize the Cartesian pose(position and attitude) of the end-effector,and the attitude of the spacecraft attaining the desired states simultaneously.The joint trajectories are parameterized by using sinusoidal polynomials functions and the cost function is proposed according to the accuracy requirements.The path planning problem is transformed to a nonlinear optimization problem.The quantum-behaved particle swarm optimization(QPSO)algorithm is employed to search for the global optimal resolution of the parameters variables.The parameters variables are taken into joint trajectories functions to realize non-holonomic path planning.A dynamic model of a space robot system composed of a spacecraft and a 6-DOF manipulator is developed,and the proposed method is verified by using this model.The simulation results show that this method is better than other approaches both in convergence rate and accuracy and the joints trajectories are very smooth and suitable for control.

Motion analysis of a spherical mobile robot

SUMMARYA path planning algorithm for a spherical mobile robot rolling on a plane is presented in this paper. The robot is actuated by two internal rotors that are fixed to the shafts of two motors. These are in turn mounted on the spherical shell in mutually orthogonal directions. The system is nonholonomic due to the nonintegrable nature of the rolling constraints. Further, the system cannot be converted into a chained form, and neither is it nilpotent nor differentially flat. So existing techniques of nonholonomic path planning cannot be applied directly to the system. The approach presented here uses simple geometrical notions and provides numerically efficient and intuitive solutions. We also present the dynamic model and derive motor torques for execution of the algorithm. Along the proposed paths, we achieve dynamic decoupling of the variables making the algorithm more suitable for practical applications.

Reliable Robust Path Planning with Application to Mobile Robots

Reliable Robust Path Planning with Application to Mobile RobotsThis paper is devoted to path planning when the safety of the system considered has to be guaranteed in the presence of bounded uncertainty affecting its model. A new path planner addresses this problem by combining Rapidly-exploring Random Trees (RRT) and a set representation of uncertain states. An idealized algorithm is presented first, before a description of one of its possible implementations, where compact sets are wrapped into boxes. The resulting path planner is then used for nonholonomic path planning in robotics.

Non-holonomic Path Planning of a Free-Floating Space Robotic System Using Genetic Algorithms

In this paper, the non-holonomic characteristic of a free-floating space robotic system is used to plan the path of the manipulator joints, by whose motion the base attitude and the manipulator joints attain the desired states. Here, we parameterize the joint trajectory using sinusoidal functions, whose arguments are high-order polynomials. Then, we define the cost function for optimization according to the constraint conditions and the accuracy of the space robot. Finally, genetic algorithms (GAs) are used to search for the solutions of the parameters. Compared with others, our approach has advantages as follows. (i) The motion of the manipulator and the disturbance on the base are practically constrained. (ii) The dynamic singularities cannot affect the algorithm since only the direct kinematic equations are utilized. (iii) The planned path is smooth and more applicable for the control of the manipulator. (iv) The convergence of the algorithm is not affected by the attitude singularity since the orientation error is represented by quaternion, which is globally singularity-free. The simulation results of the spacecraft with a 6-d.o.f. manipulator verify the performance and the validity of the proposed method.

Nonholonomic path planning among obstacles subject to curvature restrictions

This paper addresses the problem of finding a nonholonomic path subject to a curvature restriction, to be tracked by a wheeled autonomous navigation vehicle. This robot is able to navigate in a structured environment, with obstacles modeled as polygons, thus constituting a model based system. The path planning methodology begins with the conditioning of the polygonal environment by offsetting each polygon in order to avoid the possibility of collision with the mobile. Next, the modified polygonal environment is used to compute a preliminary shortest path (PA) between the two extreme positions of the trajectory in the plane (x, y). This preliminary path (PA) does not yet consider the restrictions on the curvature and is formed only by straight line segments. A smoothing process follows in order to obtain a path (PS) that satisfies curvature restrictions which consist basically of joining the straight line segments by circular arcs of minimum radius R (filleting). Finally, the initial and final orientation of the vehicle are accounted for. This is done using a technique we have called the Star Algorithm, because of the geometric shape of the resulting maneuvers. A final complete path (PC) is thus obtained.

ＥＴＳ‐ＶＩＩを用いた宇宙ロボット制御実験

This paper presents the flight experiments on the dynamics and control of a space robotic arm mounted on ETS-VII (Engineering Test Satellite VII). The experiments were successfully carried out to evaluate the performance of (1) reaction null-space based reactionless manipulation, (2) generalized Jacobian based inertial manipulation, (3) offset command based feedforward attitude control, and (4) bi-directional approach of non-holonomic path planning. Inertia parameters of ETS-VII is identified based on the momentum equation and the effect of gravity gradient torque is also evaluated.

Nonholonomic path planning of space robots via a bidirectional approach

The path planning of nonholonomic motion of space robot systems is discussed. A space vehicle with a 6-DOF (degrees of freedom) manipulator is described as a nine-variable system with six inputs. It is shown that, by carefully utilizing the nonholonomic mechanical structure, the vehicle orientation in addition to the joint variables of the manipulator can be controlled by actuating only the joint variables. The nonholonomic mechanical structure of space robot systems is shown. A rigorous mathematical proof of the nonholonomic nature of the free-flying space robot systems is provided using Frobenius's theorem. A method for nonholonomic motion planning for space robot systems is established by using a Lyapunov function.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>