A new motion planning method for discretely actuated hyper-redundant manipulators

Robotica ◽  
2015 ◽  
Vol 35 (1) ◽  
pp. 101-118 ◽  
Author(s):  
Alireza Motahari ◽  
Hassan Zohoor ◽  
Moharam Habibnejad Korayem
Keyword(s):  
Genetic Algorithm ◽  
Motion Planning ◽  
Trajectory Tracking ◽  
Inverse Kinematic ◽  
Planning Problem ◽  
Redundant Manipulators ◽  
Tracking Problem ◽  
Parallel Mechanisms ◽  
Redundant Manipulator ◽  
The Common

SUMMARYA hyper-redundant manipulator is made by mounting the serial and/or parallel mechanisms on top of each other as modules. In discrete actuation, the actuation amounts are a limited number of certain values. It is not feasible to solve the kinematic analysis problems of discretely actuated hyper-redundant manipulators (DAHMs) by using the common methods, which are used for continuous actuated manipulators. In this paper, a new method is proposed to solve the trajectory tracking problem in a static prescribed obstacle field. To date, this problem has not been considered in the literature. Theremoving first collision(RFC) method, which is originally proposed for solving the inverse kinematic problems in the obstacle fields was modified and used to solve the motion planning problem. For verification, the numerical results of the proposed method were compared with the results of thegenetic algorithm(GA) method. Furthermore, a novel DAHM designed and implemented by the authors is introduced.

Motion Planning of a Nonholonomic Multibody System Using Genetic Algorithm

2003 ◽  
Author(s):  
Xin-Sheng Ge ◽  
Li-Qun Chen
Keyword(s):  
Genetic Algorithm ◽  
Motion Planning ◽  
Nonholonomic System ◽  
Multibody System ◽  
Planning Problem ◽  
Control Approach ◽  
Velocity Constraints ◽  
Nonholonomic Motion Planning ◽  
Optimal Control Approach ◽  
Motion Planning Problem

The motion planning problem of a nonholonomic multibody system is investigated. Nonholonomicity arises in many mechanical systems subject to nonintegrable velocity constraints or nonintegrable conservation laws. When the total angular momentum is zero, the control problem of system can be converted to the motion planning problem for a driftless control system. In this paper, we propose an optimal control approach for nonholonomic motion planning. The genetic algorithm is used to optimize the performance of motion planning to connect the initial and final configurations and to generate a feasible trajectory for a nonholonomic system. The feasible trajectory and its control inputs are searched through a genetic algorithm. The effectiveness of the genetic algorithm is demonstrated by numerical simulation.

scholarly journals A sampling-based optimized algorithm for task-constrained motion planning

2019 ◽  
Vol 16 (3) ◽  
pp. 172988141984737 ◽  
Author(s):  
Kai Mi ◽  
Haojian Zhang ◽  
Jun Zheng ◽  
Jianhua Hu ◽  
Dengxiang Zhuang ◽  
...  
Keyword(s):  
Motion Planning ◽  
Sampling Methods ◽  
Tracking Error ◽  
Joint Space ◽  
Planning Problem ◽  
Redundant Manipulators ◽  
Task Space ◽  
Constrained Motion ◽  
Smooth Path ◽  
Planning Algorithm

We consider a motion planning problem with task space constraints in a complex environment for redundant manipulators. For this problem, we propose a motion planning algorithm that combines kinematics control with rapidly exploring random sampling methods. Meanwhile, we introduce an optimization structure similar to dynamic programming into the algorithm. The proposed algorithm can generate an asymptotically optimized smooth path in joint space, which continuously satisfies task space constraints and avoids obstacles. We have confirmed that the proposed algorithm is probabilistically complete and asymptotically optimized. Finally, we conduct multiple experiments with path length and tracking error as optimization targets and the planning results reflect the optimization effect of the algorithm.

scholarly journals Inverse kinematics-based motion planning for dual-arm robot with orientation constraints

2019 ◽  
Vol 16 (2) ◽  
pp. 172988141983685 ◽  
Author(s):  
Jiangping Wang ◽  
Shirong Liu ◽  
Botao Zhang ◽  
Changbin Yu
Keyword(s):  
Motion Planning ◽  
Joint Space ◽  
Inverse Kinematic ◽  
Planning Problem ◽  
Constraint Manifold ◽  
Wide Range ◽  
Planning Algorithm ◽  
Motion Paths ◽  
Dual Arm Robot ◽  
Dual Arm

This article proposes an efficient and probabilistic complete planning algorithm to address motion planning problem involving orientation constraints for decoupled dual-arm robots. The algorithm is to combine sampling-based planning method with analytical inverse kinematic calculation, which randomly samples constraint-satisfying configurations on the constraint manifold using the analytical inverse kinematic solver and incrementally connects them to the motion paths in joint space. As the analytical inverse kinematic solver is applied to calculate constraint-satisfying joint configurations, the proposed algorithm is characterized by its efficiency and accuracy. We have demonstrated the effectiveness of our approach on the Willow Garage’s PR2 simulation platform by generating trajectory across a wide range of orientation-constrained scenarios for dual-arm manipulation.

Repeatable Joint Displacement Generation for Redundant Robotic Systems

1994 ◽  
Vol 116 (1) ◽  
pp. 11-16 ◽  
Author(s):  
Y. S. Chung ◽  
M. Griffis ◽  
J. Duffy
Keyword(s):  
Joint Space ◽  
Inverse Kinematic ◽  
Torsional Stiffness ◽  
Numerical Verification ◽  
Redundant Manipulators ◽  
Redundant Manipulator ◽  
Kinematic Equation ◽  
End Effector ◽  
Prismatic Joints ◽  
Cyclic Type

This paper presents a novel, practical, and theoretically sound kinematic control strategy for serial redundant manipulators. This strategy yields repeatability in the joint space of a serial redundant manipulator whose end effector undergoes some general cyclic type motion. This is accomplished by deriving a new inverse kinematic equation that is based on springs being theoretically or conceptually located in the joints of the manipulator (torsional springs for revolute joints, translational springs for prismatic joints). Previous researchers have also derived an inverse kinematic equation for serial redundant manipulators. However, to the authors’ knowledge, the new strategy is the first to include the free angles of torsional springs and the free lengths of translational springs. This is important because it ensures the repeatability in the joint space of a serial redundant manipulator whose end effector undergoes a cyclic type motion. Numerical verification for repeatability is done in terms of Lie bracket condition. Choices for the free angle and torsional stiffness of a joint (or the free length and translational stiffness) are made based upon the mechanical limits of the joint.

Trajectory Generation for Redundant Manipulator using Virus-Evolutionary Genetic Algorithm with Subpopulations

1997 ◽  
Vol 1 (2) ◽  
pp. 155-161
Author(s):  
Takemasa Arakawa ◽  
◽  
Toshio Fukuda ◽  
Naoyuki Kubota ◽  
Keyword(s):  
Genetic Algorithm ◽  
Genetic Information ◽  
Energy Optimization ◽  
Trajectory Generation ◽  
Redundant Manipulators ◽  
Redundant Manipulator ◽  
Theory Of Evolution ◽  
Evolutionary Genetic ◽  
Generation Problem ◽  
Virus Theory

In this paper, we apply a virus-evolutionary genetic algorithm with subpopulations (VEGAS) to a trajectory generation problem for redundant manipulators through energy optimization. VEGAS is based on the virus theory of evolution and VEGAS has some subpopulations that usually evolve independently. In the same subpopulation, a virus infects host individuals. And a virus sometimes immigrates from one subpopulation to another. The genetic information from one subpopulation propagates in another subpopulation only through immigration of the virus. The energy-optimized collision-free trajectory was found successfully using VEGAS.

Inverse Kinematics of Serial Redundant Manipulators With Locked Articulations

1995 ◽  
Author(s):  
Louis Perreault ◽  
Clément M. Gosselin
Keyword(s):  
Inverse Kinematics ◽  
General Procedure ◽  
Inverse Kinematic ◽  
Redundant Manipulators ◽  
Redundant Manipulator ◽  
Inverse Kinematic Problem

Abstract This paper presents an algorithm for the solution of the inverse kinematics of a serial redundant manipulator with one (or more) locked joint(s). To this end, a general procedure is developed for the determination of the equivalent Denavit-Hartenberg parameters of a serial manipulator with locked joints. This procedure can be applied to any serial architecture. The solution of the inverse kinematic problem for the three cases which can arise is then addressed. An example of the application of the method to a SARCOS 7-DOF manipulator is also given.

Motion planning for multiple non-holonomic robots: a geometric approach

Robotica ◽  
2008 ◽  
Vol 26 (4) ◽  
pp. 525-536 ◽  
Author(s):  
Elias K. Xidias ◽  
Nikos A. Aspragathos
Keyword(s):  
Genetic Algorithm ◽  
Euclidean Space ◽  
Motion Planning ◽  
Optimization Problem ◽  
Geometric Approach ◽  
Dynamic Environments ◽  
Planning Problem ◽  
Geometrical Approach ◽  
Moving Obstacles ◽  
Geometric Entity

SUMMARYIn this paper, a geometrical approach is developed to generate simultaneously optimal (or near-optimal) smooth paths for a set of non-holonomic robots, moving only forward in a 2D environment cluttered with static and moving obstacles. The robots environment is represented by a 3D geometric entity called Bump-Surface, which is embedded in a 4D Euclidean space. The multi-motion planning problem (MMPP) is resolved by simultaneously finding the paths for the set of robots represented by monoparametric smooth C2 curves onto the Bump-Surface, such that their inverse images onto the initial 2D workspace satisfy the optimization motion-planning criteria and constraints. The MMPP is expressed as an optimization problem, which is solved on the Bump-Surface using a genetic algorithm. The performance of the proposed approach is tested through a considerable number of simulated 2D dynamic environments with car-like robots.

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