Task Space Trajectory Planning for Robot Manipulators to Follow 3-D Curved Contours

The demand for robots has increased in the industrial field, where robots are utilized in tasks that require them to move through complex paths. In the motion planning of a manipulator, path planning is carried out to determine a series of the positions of robot end effectors without collision. Therefore, it is necessary to carry out trajectory planning to determine position, velocity, and acceleration over time and to control an actual industrial manipulator. Although several methods have already been introduced for point-to-point trajectory planning, a trajectory plan which moves through multiple knots is required to allow robots to adapt to more complicated tasks. In this study, a trajectory planning based on the Catmull–Rom spline is proposed to allow a robot to move via several points in a task space. A method is presented to assign intermediate velocities and time to satisfy the velocity conditions of initial and final knots. To optimize the motion of the robot, a time-scaling method is presented to minimize the margin between the physical maximum values of velocity and acceleration in real robots and the planned trajectory, respectively. A simulation is then performed to verify that the proposed method can plan the trajectory for moving multiple knots without stopping, and also to check the effects of control parameters. The results obtained show that the proposed methods are applicable to trajectory planning and require less computation compared with the cubic spline method. Furthermore, the robot follows the planned trajectory, and its motion does not exceed the maximum values of velocity and acceleration. An experiment is also executed to prove that the proposed method can be applied to real robotic tasks to dispense glue onto the sole in the shoe manufacturing process. The results from this experiment show that the robot can follow the 3-D curved contour in uniform speed using the proposed method.

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Time-scaling of trajectories for point-to-point robotic tasks

ISA Transactions ◽

10.1016/s0019-0578(07)60221-3 ◽

2006 ◽

Vol 45 (3) ◽

pp. 407-418 ◽

Cited By ~ 9

Author(s):

Javier Moreno-Valenzuela

Keyword(s):

Time Scaling ◽

Point To Point ◽

Robotic Tasks

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Integrated Trajectory Planning and Sloshing Suppression for Three-Dimensional Motion of Liquid Container Transfer Robot Arm

Journal of Robotics ◽

10.1155/2015/279460 ◽

2015 ◽

Vol 2015 ◽

pp. 1-15 ◽

Cited By ~ 9

Author(s):

Wisnu Aribowo ◽

Takahito Yamashita ◽

Kazuhiko Terashima

Keyword(s):

Trajectory Planning ◽

Dimensional Space ◽

Translational Motion ◽

Three Dimensional ◽

Joint Space ◽

Robot Arm ◽

Task Space ◽

Robot Wrist ◽

Point To Point ◽

Sloshing Suppression

For liquid transfer system in three-dimensional space, the use of multijoint robot arm provides much flexibility. To realize quick point-to-point motion with minimal sloshing in such system, we propose an integrated framework of trajectory planning and sloshing suppression. The robot motion is decomposed into translational motion of the robot wrist and rotational motion of the robot hand to ensure the upright orientation of the liquid container. The trajectory planning for the translational motion is based on cubic spline optimization with free via points that produces smooth trajectory in joint space while it still allows obstacle avoidance in task space. Input shaping technique is applied in the task space to suppress the motion induced sloshing, which is modeled as spherical pendulum with moving support. It has been found through simulations and experiments that the proposed approach is effective in generating quick motion with low amount of sloshing.

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Virtual-mechanism-based analysis of cooperative manipulation

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1243/095440604x16830 ◽

2005 ◽

Vol 219 (3) ◽

pp. 315-323

Author(s):

H Liu ◽

J S Dai ◽

H Y Xu ◽

H Li

Keyword(s):

Trajectory Planning ◽

Manipulation Planning ◽

End Points ◽

New Approach ◽

Cooperative Manipulation ◽

Hypothetical Mechanism ◽

End Effectors ◽

Cooperative Manipulators ◽

Mechanism Theory

This paper proposes a new approach for analysing cooperative manipulation in which cooperative manipulators form a mechanism closure that allows a virtual-mechanism-based analysis to take place. The method is based on the geometry of manipulators during manipulation and converts the cooperative manipulation problem into the analysis of a hypothetical mechanism so that the mechanism theory can be used for the manipulation. This mechanism is hence generated by the fact that the end points (or geometric centres of respective grippers) of cooperative manipulators coincide with a virtual joint during cooperative manipulation. The analysis not only generates positions and orientations of the end effectors of cooperative manipulators but also produces corresponding link configurations that can be used for manipulation planning. The approach is further used for the orientation-based trajectory planning with two different cases. Simulations and discussions are made with respect to cooperative manipulations using two 2R manipulators and one 2R manipulators and one 3R manipulator.

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Motor learning in reaching tasks leads to homogenization of task space error distribution

10.1101/2021.09.01.458189 ◽

2021 ◽

Author(s):

Puneet Singh ◽

Oishee Ghosal ◽

Aditya Murthy ◽

Ashitava Ghodal

Keyword(s):

Motor Learning ◽

Force Field ◽

Error Distribution ◽

Task Space ◽

Field Perturbation ◽

Directional Dependence ◽

Reaching Tasks ◽

Space Error ◽

Human Arm ◽

Point To Point

A human arm, up to the wrist, is often modelled as a redundant 7 degree-of-freedom serial robot. Despite its inherent nonlinearity, we can perform point-to-point reaching tasks reasonably fast and with reasonable accuracy in the presence of external disturbances and noise. In this work, we take a closer look at the task space error during point-to-point reaching tasks and learning during an external force-field perturbation. From experiments and quantitative data, we confirm a directional dependence of the peak task space error with certain directions showing larger errors than others at the start of a force-field perturbation, and the larger errors are reduced with repeated trials implying learning. The analysis of the experimental data further shows that a) the distribution of the peak error is made more uniform across directions with trials and the error magnitude and distribution approaches the value when no perturbation is applied, b) the redundancy present in the human arm is used more in the direction of the larger error, and c) homogenization of the error distribution is not seen when the reaching task is performed with the non-dominant hand. The results support the hypothesis that not only magnitude of task space error, but the directional dependence is reduced during motor learning and the workspace is homogenized possibly to increase the control efficiency and accuracy in point-to-point reaching tasks. The results also imply that redundancy in the arm is used to homogenize the workspace, and additionally since the bio-mechanically similar dominant and non-dominant arms show different behaviours, the homogenizing is actively done in the central nervous system.

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