scholarly journals A Constraint-Aware Motion Planning Algorithm for Robotic Folding of Clothes

2013 ◽  
pp. 547-562 ◽  
Author(s):  
Karthik Lakshmanan ◽  
Apoorva Sachdev ◽  
Ziang Xie ◽  
Dmitry Berenson ◽  
Ken Goldberg ◽  
...  
Keyword(s):  
Motion Planning ◽  
Planning Algorithm

scholarly journals A new method on motion planning for mobile robots using jump point search and Bezier curves

2021 ◽  
Vol 18 (4) ◽  
pp. 172988142110192
Author(s):  
Ben Zhang ◽  
Denglin Zhu
Keyword(s):  
Motion Planning ◽  
Initial Point ◽  
Target Point ◽  
Jump Point ◽  
Bezier Curves ◽  
Bézier Curves ◽  
Front End ◽  
Planning Algorithm ◽  
Point Search ◽  
Path Planning Algorithm

Innovative applications in rapidly evolving domains such as robotic navigation and autonomous (driverless) vehicles rely on motion planning systems that meet the shortest path and obstacle avoidance requirements. This article proposes a novel path planning algorithm based on jump point search and Bezier curves. The proposed algorithm consists of two main steps. In the front end, the improved heuristic function based on distance and direction is used to reduce the cost, and the redundant turning points are trimmed. In the back end, a novel trajectory generation method based on Bezier curves and a straight line is proposed. Our experimental results indicate that the proposed algorithm provides a complete motion planning solution from the front end to the back end, which can realize an optimal trajectory from the initial point to the target point used for robot navigation.

scholarly journals Sampling-Based Motion Planning for Free-Floating Space Robot without Inverse Kinematics

2020 ◽  
Vol 10 (24) ◽  
pp. 9137
Author(s):  
Hongwen Zhang ◽  
Zhanxia Zhu
Keyword(s):  
Motion Planning ◽  
Inverse Kinematics ◽  
Random Trees ◽  
Space Robot ◽  
Initial Configuration ◽  
First Order ◽  
System A ◽  
Planning Framework ◽  
Planning Algorithm ◽  
Differential Relationship

Motion planning is one of the most important technologies for free-floating space robots (FFSRs) to increase operation safety and autonomy in orbit. As a nonholonomic system, a first-order differential relationship exists between the joint angle and the base attitude of the space robot, which makes it pretty challenging to implement the relevant motion planning. Meanwhile, the existing planning framework must solve inverse kinematics for goal configuration and has the limitation that the goal configuration and the initial configuration may not be in the same connected domain. Thus, faced with these questions, this paper investigates a novel motion planning algorithm based on rapidly-exploring random trees (RRTs) for an FFSR from an initial configuration to a goal end-effector (EE) pose. In a motion planning algorithm designed to deal with differential constraints and restrict base attitude disturbance, two control-based local planners are proposed, respectively, for random configuration guiding growth and goal EE pose-guiding growth of the tree. The former can ensure the effective exploration of the configuration space, and the latter can reduce the possibility of occurrence of singularity while ensuring the fast convergence of the algorithm and no violation of the attitude constraints. Compared with the existing works, it does not require the inverse kinematics to be solved while the planning task is completed and the attitude constraint is preserved. The simulation results verify the effectiveness of the algorithm.

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

2016 ◽  
Vol 40 (3) ◽  
pp. 383-397 ◽  
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.

Motion Planning of an Innovative Serial Robot for Energy Consumption Reduction With “On Fly” Pieces Grasping

2008 ◽  
Author(s):  
Andrea Menegolo ◽  
Roberto Bussola ◽  
Diego Tosi
Keyword(s):  
Energy Consumption ◽  
Motion Planning ◽  
Cycle Time ◽  
Moving Objects ◽  
Vision System ◽  
Rotation Velocity ◽  
Simulation Software ◽  
Serial Robot ◽  
Planning Algorithm ◽  
Point To Point

The following study deals with the on-line motion planning of an innovative SCARA like robot with unlimited joint rotations. The application field is the robotic interception of moving objects randomly distributed on a conveyor and detected by a vision system. A motion planning algorithm was developed in order to achieve a satisfactory cycle time and energy consumption. The algorithm is based on the evaluation of the inertial actions arisen in the robot structure during the pick and place motions and it aims to keep constant the rotation velocity of the first joint during the motion, the grasping and the discarding phases. Since the algorithm must be applied run time and the number of the reachable pieces can be high, a particular care was dedicated to the computational burden reduction. Subsequently to an analytic study of the kinematical constraints and the criteria definition for the choice of which piece to grasp, a devoted simulation software was developed. The software allows the control and the evaluation of the effects of all the main parameters on the system behavior and a comparison of the cycle time and the energy consumption between the proposed algorithm and a standard point-to-point motion strategy.

Feedback motion planning of unmanned surface vehicles via random sequential composition

2019 ◽  
Vol 41 (12) ◽  
pp. 3321-3330 ◽  
Author(s):  
Emre Ege ◽  
Mustafa Mert Ankarali
Keyword(s):  
Motion Planning ◽  
Broad Class ◽  
Random Trees ◽  
Main Approach ◽  
Unmanned Surface Vehicles ◽  
Sequential Composition ◽  
Planning Algorithm ◽  
Overall Performance ◽  
Simulation Results ◽  
Feasible Solutions

In this paper, we propose a new motion planning method that aims to robustly and computationally efficiently solve path planning and navigation problems for unmanned surface vehicles (USVs). Our approach is based on synthesizing two different existing methodologies: sequential composition of dynamic behaviours and rapidly exploring random trees (RRT). The main motivation of this integrated solution is to develop a robust feedback-based and yet computationally feasible motion planning algorithm for USVs. In order to illustrate the main approach and show the feasibility of the method, we performed simulations and tested the overall performance and applicability for future experimental applications. We also tested the robustness of the method under relatively extreme environmental uncertainty. Simulation results indicate that our method can produce robust and computationally feasible solutions for a broad class of USVs.

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