Avoidability measure in moving obstacle avoidance problem and its use for robot motion planning

2002 ◽  
Author(s):  
Nak Yong Ko ◽  
Bum Hee Lee
Keyword(s):  
Motion Planning ◽  
Obstacle Avoidance ◽  
Robot Motion ◽  
Robot Motion Planning ◽  
Moving Obstacle ◽  
Avoidance Problem

An approach to robot motion planning for time-varying obstacle avoidance using the view-time concept

Robotica ◽  
1993 ◽  
Vol 11 (4) ◽  
pp. 315-327 ◽  
Author(s):  
Nak Yong Ko ◽  
Bum Hee Leet ◽  
Myoung Sam Kot
Keyword(s):  
Motion Planning ◽  
Obstacle Avoidance ◽  
Shape Change ◽  
Robotic Manipulator ◽  
Joint Space ◽  
Robot Motion ◽  
Robot Motion Planning ◽  
Time Varying ◽  
Solution Approach ◽  
Moving Obstacle

SUMMARYAn analytic solution approach to the time-varying obstacle avoidance problem is adopted. The problem considers the collision between any link of the robotic manipulator and the time-varying obstacle. The information on the motion and shape change of the obstacle is given prior to robot motion planning. To facilitate the problem, we analyze and formulate it mathematically in a robot joint space. We then introduce the view-time concept and analyze its properties. Using the properties of the view-time, a view-time based motion planning method is proposed. The view-time based method plans the robot motion by units of the view-time. In every view-time, it uses a stationary obstacle avoidance scheme. The proposed method is applied to the motion planning of a 2 DOF robotic manipulator in an environment with a polyhedral moving obstacle.

Probabilistic Uncertainty Modeling of Obstacle Motion for Robot Motion Planning

2002 ◽  
Vol 14 (4) ◽  
pp. 349-356 ◽  
Author(s):  
Jun Miura ◽  
◽  
Yoshiaki Shirai
Keyword(s):  
Motion Planning ◽  
Uncertainty Modeling ◽  
Robot Motion ◽  
Robot Motion Planning ◽  
Probabilistic Uncertainty ◽  
Probabilistic Distribution ◽  
Uncertainty Model ◽  
Observation Uncertainty ◽  
Moving Obstacle ◽  
Time Point

This paper describes a method of modeling the motion uncertainty of moving obstacles and its application to mobile robot motion planning. The method explicitly considers three sources of uncertainty: path ambiguity, velocity uncertainty, and observation uncertainty. In the uncertainty model, the position of an obstacle at a certain time point is represented by a probabilistic distribution over possible positions on each possible path of the moving obstacle. Using this model, the best robot motion is selected in a decision-theoretic way. By considering the distribution, not the range, of uncertainty, more efficient behavior of the robot is realized.

scholarly journals The Use of Self-Organizing Cells in Robot Motion Planning

1994 ◽  
Vol 6 (6) ◽  
pp. 479-484
Author(s):  
Toshifumi Satake ◽  
◽  
Akihiro Hayashi ◽  
Hiroshi Suzuki
Keyword(s):  
Motion Planning ◽  
Obstacle Avoidance ◽  
Artificial Life ◽  
Control Mechanism ◽  
Robot Motion ◽  
Robot Motion Planning ◽  
Use Of Self ◽  
Intelligent Robots ◽  
Planning Algorithm ◽  
Autonomous Elements

Robot motion planning including obstacle avoidance is a necessary technique for realizing autonomous intelligent robots. In this study, a robot motion planning algorithm has been developed by applying the organic mechanisms such as artificial life (AL) and GAs. The proposed concept represents a robot as a combination of several groups composed of a set of cells defined as autonomous elements like a living thing. Robot motion is determined as the result of behavior that individual cells avoid obstacles, and they then organize themselves as forming a geometric shape of component parts of a robot according to the control mechanism given to each cell. This paper describes the preliminary concepts of the Obstacle Avoidance and Self Organization in the proposed methodology for generating collision-free motion of a robot and the details of the developed algorithm based on these concepts. To estimate the effectiveness of the proposed idea, simple case studies of the motion planning for mobile robot have been executed.

scholarly journals MULTI-ROBOT MOTION PLANNING: A MODIFIED RECEDING HORIZON APPROACH FOR REACHING GOAL STATES

2016 ◽  
Vol 56 (1) ◽  
pp. 10 ◽  
Author(s):  
José M. Mendes Filho ◽  
Eric Lucet
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Travel Time ◽  
Real Time ◽  
Obstacle Avoidance ◽  
Computation Time ◽  
Robot Motion ◽  
Robot Motion Planning ◽  
Receding Horizon ◽  
Different Shapes

This paper proposes the real-time implementation of an algorithm for collision-free motion planning based on a receding horizon approach, for the navigation of a team of mobile robots in presence of obstacles of different shapes. The method is simulated with three robots. Impact of parameters is studied with regard to computation time, obstacle avoidance and travel time.

Sign in / Sign up

Export Citation Format

Share Document