Augmenting human performance in motion planning tasks-the configuration space approach

2002 ◽  
Author(s):  
I. Ivanisevic ◽  
V. Lumelsky
Keyword(s):  
Motion Planning ◽  
Configuration Space ◽  
Human Performance ◽  
Space Approach

Motion planning of the trident snake robot equipped with passive or active wheels

2012 ◽  
Vol 60 (3) ◽  
pp. 547-555 ◽  
Author(s):  
D. Paszuk ◽  
K. Tchoń ◽  
Z. Pietrowska
Keyword(s):  
Control System ◽  
Motion Planning ◽  
Computer Simulations ◽  
Configuration Space ◽  
Snake Robot ◽  
System Representation ◽  
And Control ◽  
Planning Problems ◽  
Jacobian Algorithm ◽  
Space Approach

Abstract We study the kinematics of the trident snake robot equipped with either active joints and passive wheels or passive joints and active wheels. A control system representation of the kinematics is derived, and control singularities examined. Two motion planning problems are addressed, corresponding to diverse ways of controlling the robot, and solved by means of the endogenous configuration space approach. The constraints imposed by the presence of control singularities are handled using the imbalanced Jacobian algorithm assisted by an auxiliary feedback. Performance of the motion planning algorithms is demonstrated by computer simulations.

scholarly journals On dynamically consistent Jacobian inverse for non-holonomic robotic systems

2017 ◽  
Vol 27 (4) ◽  
pp. 555-573 ◽  
Author(s):  
Joanna Ratajczak ◽  
Krzysztof Tchoń
Keyword(s):  
Motion Planning ◽  
Configuration Space ◽  
Consistency Condition ◽  
Robotic Systems ◽  
Planning Problem ◽  
Commutativity Property ◽  
Kinematic Singularities ◽  
Planning Problems ◽  
Jacobian Inverse ◽  
Space Approach

AbstractThis paper presents the dynamically consistent Jacobian inverse for non-holonomic robotic system, and its application to solving the motion planning problem. The system’s kinematics are represented by a driftless control system, and defined in terms of its input-output map in accordance with the endogenous configuration space approach. The dynamically consistent Jacobian inverse (DCJI) has been introduced by means of a Riemannian metric in the endogenous configuration space, exploiting the reduced inertia matrix of the system’s dynamics. The consistency condition is formulated as the commutativity property of a diagram of maps. Singular configurations of DCJI are studied, and shown to coincide with the kinematic singularities. A parametric form of DCJI is derived, and used for solving example motion planning problems for the trident snake mobile robot. Some advantages in performance of DCJI in comparison to the Jacobian pseudoinverse are discovered.

scholarly journals Task-priority motion planning of underactuated systems: an endogenous configuration space approach – ERRATUM

Robotica ◽  
2010 ◽  
Vol 28 (6) ◽  
pp. 943-943
Author(s):  
Adam Ratajczak ◽  
Joanna Karpińska ◽  
Krzysztof Tchoń
Keyword(s):  
Motion Planning ◽  
Configuration Space ◽  
Underactuated Systems ◽  
Single Task ◽  
Correct Form ◽  
Task Priority ◽  
Image Position ◽  
Priority Algorithm ◽  
Space Approach

Figures 2 and 5 were incorrectly reproduced in the above publication (Ratajczak et al. 2009). The figures are reproduced below in their correct form. Fig. 2.Task-priority algorithm (both S1 and S2).Fig. 5.Single-task algorithm (only S1).

Task-priority motion planning of underactuated systems: an endogenous configuration space approach

Robotica ◽  
2009 ◽  
Vol 28 (6) ◽  
pp. 885-892 ◽  
Author(s):  
Adam Ratajczak ◽  
Joanna Karpińska ◽  
Krzysztof Tchoń
Keyword(s):  
Motion Planning ◽  
Configuration Space ◽  
Robotic Systems ◽  
Planning Problem ◽  
Redundant Manipulators ◽  
Container Ship ◽  
Secondary Tasks ◽  
Planning Algorithm ◽  
Task Priority ◽  
Space Approach

SUMMARYThis paper presents a task-priority motion planning algorithm for underactuated robotic systems. The motion planning algorithm combines two features: the idea of the task-priority control of redundant manipulators and the endogenous configuration space approach. This combination results in the algorithm which solves the primary motion planning task simultaneously with one or more secondary tasks ordered in accordance with decreasing priorities. The performance of the task-priority motion planning algorithm has been illustrated with computer simulations of the motion planning problem for a container ship.

scholarly journals Normal form approach in the motion planning of space robots: a case study

2021 ◽  
Author(s):  
Krzysztof Tchoń ◽  
Katarzyna Zadarnowska
Keyword(s):  
Normal Form ◽  
Motion Planning ◽  
Normal Forms ◽  
Inverse Dynamics ◽  
Planning Problem ◽  
Inverse Dynamics Problem ◽  
Velocity Level ◽  
Form Approach ◽  
Space Approach

AbstractWe examine applicability of normal forms of non-holonomic robotic systems to the problem of motion planning. A case study is analyzed of a planar, free-floating space robot consisting of a mobile base equipped with an on-board manipulator. It is assumed that during the robot’s motion its conserved angular momentum is zero. The motion planning problem is first solved at velocity level, and then torques at the joints are found as a solution of an inverse dynamics problem. A novelty of this paper lies in using the chained normal form of the robot’s dynamics and corresponding feedback transformations for motion planning at the velocity level. Two basic cases are studied, depending on the position of mounting point of the on-board manipulator. Comprehensive computational results are presented, and compared with the results provided by the Endogenous Configuration Space Approach. Advantages and limitations of applying normal forms for robot motion planning are discussed.

ADD-RRV for motion planning in complex environments

Robotica ◽  
2021 ◽  
pp. 1-18
Author(s):  
Peng Cai ◽  
Xiaokui Yue ◽  
Hongwen Zhang
Keyword(s):  
Principal Component Analysis ◽  
Motion Planning ◽  
Configuration Space ◽  
Principal Component ◽  
Component Analysis ◽  
Planning Method ◽  
Complex Environments ◽  
Local Configuration ◽  
Narrow Passage

Abstract In this paper, we present a novel sampling-based motion planning method in various complex environments, especially with narrow passages. We use online the results of the planner in the ADD-RRT framework to identify the types of the local configuration space based on the principal component analysis (PCA). The identification result is then used to accelerate the expansion similar to RRV around obstacles and through narrow passages. We also propose a modified bridge test to identify the entrance of a narrow passage and boost samples inside it. We have compared our method with known motion planners in several scenarios through simulations. Our method shows the best performance across all the tested planners in the tested scenarios.

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