Obstacle Avoidance for Spatial Hyper-Redundant Manipulators Using Harmonic Potential Functions and the Mode Shape Technique

2003 ◽  
Vol 20 (1) ◽  
pp. 23-33 ◽  
Author(s):  
F. Fahimi ◽  
H. Ashrafiuon ◽  
C. Nataraj
Keyword(s):  
Obstacle Avoidance ◽  
Mode Shape ◽  
Potential Functions ◽  
Harmonic Potential ◽  
Redundant Manipulators

Obstacle Avoidance for 2D Hyper-Redundant Manipulators Using Harmonic Potential Functions and the Mode Shape Technique

2001 ◽  
Author(s):  
F. Fahimi ◽  
H. Ashrafiuon ◽  
C. Nataraj
Keyword(s):  
Obstacle Avoidance ◽  
Dimensional Space ◽  
Potential Functions ◽  
Harmonic Potential ◽  
Redundant Manipulators ◽  
Two Dimensional ◽  
Algebraic Equations ◽  
Backbone Curve ◽  
Cluttered Environments ◽  
Fitting Method

Abstract Obstacle avoidance for discrete-link two-dimensional (2D) hyper-redundant manipulators in known environments is considered. The manipulator is divided into two sections, a proximal section that has not entered the space among obstacles and a distal section among the obstacles. Harmonic potential functions were used, in order to avoid local minima in cluttered environments. A modified panel method is used to generate the potential of any arbitrary shaped obstacle in two-dimensional space. An alternative backbone curve concept and an efficient fitting method are introduced to control the trajectory of proximal links. The fitting method is recursive and avoids the complications involved with solving large systems of nonlinear algebraic equations. Combination of the safe path derived from the harmonic potential field and the backbone curve concept leads to an elegant kinematic control strategy that guarantees obstacle avoidance for planar hyper-redundant robotic manipulators.

Obstacle avoidance control of a human-in-the-loop mobile robot system using harmonic potential fields

Robotica ◽  
2017 ◽  
Vol 36 (4) ◽  
pp. 463-483 ◽  
Author(s):  
C. Ton ◽  
Z. Kan ◽  
S. S. Mehta
Keyword(s):  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Sliding Mode ◽  
Harmonic Potential ◽  
Control Allocation ◽  
Control Input ◽  
Continuous Control ◽  
Control Effort ◽  
Human In The Loop ◽  
Allocation Function

SUMMARYThis paper considers applications where a human agent is navigating a semi-autonomous mobile robot in an environment with obstacles. The human input to the robot can be based on a desired navigation objective, which may not be known to the robot. Additionally, the semi-autonomous robot can be programmed to ensure obstacle avoidance as it navigates the environment. A shared control architecture can be used to appropriately fuse the human and the autonomy inputs to obtain a net control input that drives the robot. In this paper, an adaptive, near-continuous control allocation function is included in the shared controller, which continuously varies the control effort exerted by the human and the autonomy based on the position of the robot relative to obstacles. The developed control allocation function facilitates the human to freely navigate the robot when away from obstacles, and it causes the autonomy control input to progressively dominate as the robot approaches obstacles. A harmonic potential field-based non-linear sliding mode controller is developed to obtain the autonomy control input for obstacle avoidance. In addition, a robust feed-forward term is included in the autonomy control input to maintain stability in the presence of adverse human inputs, which can be critical in applications such as to prevent collision or roll-over of smart wheelchairs due to erroneous human inputs. Lyapunov-based stability analysis is presented to guarantee finite-time stability of the developed shared controller, i.e., the autonomy guarantees obstacle avoidance as the human navigates the robot. Experimental results are provided to validate the performance of the developed shared controller.

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