Motion Planning For Redundant Branching Articulated Figures With Many Degrees Of Freedom

In this paper, a mobile robot named VicRoB with 6 degrees of freedom (DOFs) driven by three tracked vehicles is designed and analyzed. The robot employs a 3-PPSR parallel configuration. The scheme of the mechanism and the inverse kinematic solution are given. A path planning method of a single tracked vehicle and a coordinated motion planning of three tracked vehicles are proposed. The mechanical structure and the electrical architecture of VicRoB prototype are illustrated. VicRoB can achieve the point-to-point motion mode and the continuous motion mode with employing the motion planning method. The orientation precision of VicRoB is measured in a series of motion experiments, which verifies the feasibility of the motion planning method. This work provides a kinematic basis for the orientation closed loop control of VicRoB whether it works on flat or rough road.

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OPTIMAL MOTION PLANNING OF A PLANAR PARALLEL MANIPULATOR WITH KINEMATICALLY REDUNDANT DEGREES OF FREEDOM

Transactions of the Canadian Society for Mechanical Engineering ◽

10.1139/tcsme-2016-0028 ◽

2016 ◽

Vol 40 (3) ◽

pp. 383-397 ◽

Cited By ~ 2

Author(s):

Bahman Nouri Rahmat Abadi ◽

Sajjad Taghvaei ◽

Ramin Vatankhah

Keyword(s):

Motion Planning ◽

Feedback Linearization ◽

Degrees Of Freedom ◽

Jacobian Matrix ◽

Redundant Manipulator ◽

Optimal Motion ◽

Planar Parallel Manipulator ◽

Optimal Motion Planning ◽

Planning Algorithm ◽

Actuation Method

In this paper, an optimal motion planning algorithm and dynamic modeling of a planar kinematically redundant manipulator are considered. Kinematics of the manipulator is studied, Jacobian matrix is obtained and the dynamic equations are derived using D’Alembert’s principle. Also, a novel actuation method is introduced and applied to the 3-PRPR planar redundant manipulator. In this approach, the velocity of actuators is determined in such a way to minimize the 2-norm of the velocity vector, subjected to the derived kinematic relations as constraints. Having the optimal motion planning, the motion is controlled via a feedback linearization controller. The motion of the manipulator is simulated and the effectiveness of the proposed actuation strategy and the designed controller is investigated.

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Take-Off Motion Planning of Legged Hopping Robot with Redundancy Characteristic

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.823.127 ◽

2013 ◽

Vol 823 ◽

pp. 127-130

Author(s):

Yong Bo Li ◽

Min Qiang Xu ◽

Yu Wei

Keyword(s):

Boundary Condition ◽

Motion Planning ◽

Inverse Kinematics ◽

Degrees Of Freedom ◽

Polynomial Interpolation ◽

Hopping Robot ◽

Continuous Scale ◽

Quartic Polynomial ◽

Driving Torque ◽

Joint Limit

The planning for four-joint legged hopping robot with two redundant degrees of freedom at the take-off stage is researched. According to the take-off velocity and the boundary condition of centroid motion, the trajectory is planned with variable quartic polynomial interpolation. From inverse kinematics, the motion planning with redundancy characteristic is completed by using the GPM with continuous scale factor. Performance index of avoiding joint limit and optimizing joint driving torque are realized. The data indicates the feasibility and practicability of this algorithm.

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Motion planning with six degrees of freedom by multistrategic bidirectional heuristic free-space enumeration

IEEE Transactions on Robotics and Automation ◽

10.1109/70.88136 ◽

1991 ◽

Vol 7 (3) ◽

pp. 267-277 ◽

Cited By ~ 84

Author(s):

K. Kondo

Keyword(s):

Motion Planning ◽

Free Space ◽

Degrees Of Freedom ◽

Six Degrees Of Freedom

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Probabilistic Roadmaps Based Motion Planning of a 4 Degree of Freedom Robot

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.241-244.1922 ◽

2012 ◽

Vol 241-244 ◽

pp. 1922-1930

Author(s):

Yu Tian Liu

Keyword(s):

Motion Planning ◽

Configuration Space ◽

Shortest Path ◽

Degrees Of Freedom ◽

Learning Phase ◽

Degree Of Freedom ◽

Motion Path ◽

Probabilistic Roadmaps ◽

Two Phases ◽

4 Degrees Of Freedom

In this paper, we used a probabilistic roadmaps(PRM) method to plan a motion path for a 4 degrees of freedom(DOF) robot in static workspace. This methods includes two phases: a learning phase and a query phase. In learning phase, a roadmap is constructed and stored as a graph , in which stores all of the random collision-free configurations in free configuration space denoted by and keeps all of the edges corresponding to feasible paths between these configurations. In query phase, the algorithm tries to connect any given initial and goal configuration to the nodes in the graph. And then the Dijkstra's algorithm searches for a shortest path to concatenate these two nodes. The experiment result demonstrates that this method applying to this 4 degrees of freedom robot works well.

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Coordinated Motion Planning of Legged Mobile Manipulator for Tracking the Given End-Effector’s Trajectory

Volume 4: Dynamics, Vibration, and Control ◽

10.1115/imece2019-11170 ◽

2019 ◽

Author(s):

Kondalarao Bhavanibhatla ◽

Sulthan Suresh-Fazeela ◽

Dilip Kumar Pratihar

Keyword(s):

Motion Planning ◽

Degrees Of Freedom ◽

Robotic System ◽

Simulation Software ◽

Body Motion ◽

Whole Body ◽

Mobile Manipulator ◽

Coordinated Motion ◽

Multibody Dynamic ◽

The Given

Abstract In this paper, a novel algorithm is presented to achieve the coordinated motion planning of a Legged Mobile Manipulator (LMM) for tracking the given end-effector’s trajectory. LMM robotic system can be obtained by mounting a manipulator on the top of a multi-legged platform for achieving the capabilities of both manipulation and mobility. To exploit the advantages of these capabilities, the manipulator should be able to accomplish the task, while the hexapod platform moves simultaneously. In the presented approach, the whole-body motion planning is achieved in two steps. In the first step, the robotic system is assumed to be a mobile manipulator, in which the manipulator has two additional translational degrees of freedom at the base. The redundancy of this robotic system is solved by treating it as an optimization problem. Then, in the second step, the omnidirectional motion of the legged platform is achieved with a combination of straight forward and crab motions. The proposed algorithm is tested through a numerical simulation in MATLAB and then, validated on a virtual model of the robot using multibody dynamic simulation software, MSC ADAMS. Multiple trajectories of the end-effector have been tested and the results show that the proposed algorithm accomplishes the given task successfully by providing a singularity-free whole-body motion.

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Motion planning in crowded planar environments

Robotica ◽

10.1017/s0263574799001629 ◽

1999 ◽

Vol 17 (4) ◽

pp. 365-371 ◽

Cited By ~ 2

Author(s):

Yoav Lasovsky ◽

Leo Joskowicz

Keyword(s):

Motion Planning ◽

Configuration Space ◽

Degrees Of Freedom ◽

Optimization Problems ◽

Linear Optimization ◽

Local Geometry ◽

Objective Functions ◽

Linear Optimization Problems ◽

Geometrically Complex ◽

Crowded Environments

We present a new algorithm for fine motion planning in geometrically complex situations. Geometrically complex situations have complex robot and environment geometry, crowded environments, narrow passages and tight fits. They require complex robot motions with coupled degrees of freedom. The algorithm constructs a path by incrementally building a graph of linearized convex configuration space cells and solving a series of linear optimization problems with varying objective functions. Its advantages are that it better exploits the local geometry of narrow passages in configuration space, and that its complexity does not significantly increase as the clearance of narrow passages decreases. We demonstrate the algorithm on examples which other planners could not solve.

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