Optimization-Based Motion Planning in Joint Space for Walking Assistance With Wearable Robot

2015 ◽  
Vol 31 (2) ◽  
pp. 415-424 ◽  
Author(s):  
Takahiro Kagawa ◽  
Hironori Ishikawa ◽  
Takayuki Kato ◽  
ChangHyun Sung ◽  
Yoji Uno
Keyword(s):  
Motion Planning ◽  
Joint Space ◽  
Wearable Robot

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.

scholarly journals Whole-Body Motion Planning for a Six-Legged Robot Walking on Rugged Terrain

2019 ◽  
Vol 9 (24) ◽  
pp. 5284 ◽  
Author(s):  
Jie Chen ◽  
Fan Gao ◽  
Chao Huang ◽  
Jie Zhao
Keyword(s):  
Motion Planning ◽  
Spline Interpolation ◽  
Stability Margin ◽  
Joint Space ◽  
Body Motion ◽  
Whole Body ◽  
Legged Robot ◽  
Rugged Terrain ◽  
The Stability ◽  
The Moment

Whole-body motion planning is a key ability for legged robots, which allows for the generation of terrain adaptive behaviors and thereby improved mobility in complex environment. To this end, this paper addresses the issue of terrain geometry based whole-body motion planning for a six-legged robot over a rugged terrain. The whole-body planning is decomposed into two sub-tasks: leg support and swing. For leg support planning, the target pose of the robot torso in a walking step is first found by maximizing the stability margin at the moment of support-swing transition and matching the orientation of the support polygon formed by target footholds. Then, the torso and thereby the leg support trajectories are generated using cubic spline interpolation and transferred into joint space through inverse kinematics. In terms of leg swing planning, the trajectories in a walking step are generated by solving an optimal problem that satisfies three constraints and a bioinspired objective function. The proposed whole-body motion planning strategies are implemented with a simulation and a real-world six-legged robot, and the results show that stable and collision-free motions can be produced for the robot over rugged terrains.

An Efficient Path-Planning Algorithm for a Robotic Manipulator by Automatic Selection Search of Indispensable Regions in Its Configuration Space

1992 ◽  
Vol 4 (5) ◽  
pp. 378-385
Author(s):  
Hiroshi Noborio ◽  
◽  
Motohiko Watanabe ◽  
Takeshi Fujii
Keyword(s):  
Path Planning ◽  
Motion Planning ◽  
Configuration Space ◽  
Robotic Manipulator ◽  
Joint Space ◽  
Practical Applications ◽  
Continuous Sequence ◽  
Angle Difference ◽  
Planning Algorithm ◽  
Path Planning Algorithm

In this paper, we propose a feasible motion planning algorithm for a robotic manipulator and its obstacles. The algorithm quickly selects a feasible sequence of collision-free motions while adaptively expanding a graph in the implicit configuration joint-space. In the configuration graph, each arc represents an angle difference of the manipulator joint; therefore, an arc sequence represents a continuous sequence of robot motions. Thus, the algorithm can execute a continuous sequence of collision-free motions. Furthermore, the algorithm expands the configuration graph only in space which is to be cluttered in the implicit configuration joint-space and which is needed to select a collision-free sequence between the initial and target positions/orientations. The algorithm maintains the configuration graph in a small size and quickly selects a collision-free sequence from the configuration graph, whose shape is to be simple enough to move the manipulator in practical applications.

JOINT SPACE POINT-TO-POINT MOTION PLANNING FOR ROBOTS. AN INDUSTRIAL IMPLEMENTATION

2005 ◽  
Vol 38 (1) ◽  
pp. 187-192
Author(s):  
Gianluca Antonelli ◽  
Stefano Chiaverini ◽  
Marco Palladino ◽  
Gian Paolo Gerio ◽  
Gerardo Renga
Keyword(s):  
Motion Planning ◽  
Joint Space ◽  
Industrial Implementation ◽  
Point Motion ◽  
Space Point ◽  
Point To Point

scholarly journals Combined dynamics and kinematics networked fuzzy task priority motion planning for underwater vehicle-manipulator systems

2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110122
Author(s):  
Yanhui Wei ◽  
Yongkang Hou ◽  
Shanshan Luo ◽  
Qiangqiang Li ◽  
Jishun Xie
Keyword(s):  
Motion Planning ◽  
Sliding Mode ◽  
Null Space ◽  
External Disturbance ◽  
Dynamic Control ◽  
Underwater Vehicle ◽  
Joint Space ◽  
Transformation Method ◽  
Coordinated Motion ◽  
Task Priority

The underwater vehicle-manipulator systems (UVMS) face significant challenges in trajectory tracking and motion planning because of external disturbance (current and payload) and kinematic redundancy. Former algorithms can finish the tracking of end-effector (EE) and free of singularity redundancy solution alone. However, only a few analytical studies have been conducted on coordinated motion planning of UVMS considering the dynamics controller. This article introduces a combined dynamics and kinematics networked fuzzy task priority motion planning method to solve the above problems. It avoids the assumption of perfect dynamic control. Firstly, to eliminate the kinematics error, a dynamic transformation method from joint space to task space is proposed. Without chattering, an outer loop sliding mode controller is designed for tracking EE’s trajectory. Further, to ensure the underwater vehicle’ posture stability and joint constraint, a task priority frame with kinematics error is used to planning the coordinated motion of UVMS, in which the posture and joint limits map into the null space of prioritized tasks, and weight gains are adopted to guarantee orthogonality of secondary tasks. On top of that, the gain weighted are updated by the networked fuzzy logic. The proposed algorithm achieves better coordinated motion planning and tracking performance. Effectiveness is validated by numerical simulation.

Human-Like Motion Planning for a 4-DOF Anthropomorphic Arm Based on Arm’s Inherent Characteristics

2017 ◽  
Vol 14 (04) ◽  
pp. 1750005 ◽  
Author(s):  
Hongcheng Xu ◽  
Xilun Ding
Keyword(s):  
Motion Planning ◽  
Joint Space ◽  
Cartesian Space ◽  
Novel Approach ◽  
Point Motion ◽  
Human Likeness ◽  
Fixed Axis ◽  
Point To Point ◽  
The Brain ◽  
Basic Motion

Human-likeness of an anthropomorphic arm is mainly exhibited by the main arm consisting of shoulder and elbow joints as well as upper arm and forearm. In this paper, we focus on a 4-DOF anthropomorphic arm and propose a novel approach to generate human-like motion, considering human physiological and psychological factors. According to the features of musculoskeletal system of human upper limb, the 3-DOF shoulder joint is simplified with two rotations: one is about a fixed axis through shoulder center and the other is about the axis of humerus. In addition with elbow joint and a special rotation about the shoulder-wrist line, they constitute the basic motion primitives (MPs) which are macroscopic compared with the joint space but microscopic compared with the Cartesian space. Therefore, planning motion based on MPs combines intuitiveness and flexibility. Two basic kinds of motion planning, point-to-point motion planning and linear trajectory planning, are conducted. The different psychological concerns, i.e., predicting the next step of configuration and relieving the brain burden, are taken into account. Simulations are performed to verify the feasibility and validation of the proposed approach. Comparisons between simulation results with the proposed method and that with traditional joint and Cartesian space methods prove the improvement in human-likeness.

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