Authors:
Burak Boyacioglu
and
Seniz Ertugrul
Affiliation:
Istanbul Technical University, Turkey
Keyword(s):
Trajectory Planning, RRT, Smoothing, Jerk Limitation, Time Optimality, Manipulators.
Related
Ontology
Subjects/Areas/Topics:
Humanoid Robots
;
Informatics in Control, Automation and Robotics
;
Robot Design, Development and Control
;
Robotics and Automation
Abstract:
Trajectory planning is one of the most studied topics in robotics. Among several methods, a sampling-based
method, Rapidly-exploring Randomized Tree (RRT) algorithm, has become popular over the last two decades
due to its computational efficiency. However, the RRT method does not suggest an exact way to obtain a
smooth trajectory along the viapoints given by itself. In this paper, we present an approach using a timeoptimal
trajectory planning algorithm, specifically for robotic manipulators without using inverse kinematics.
After the trajectory smoothing with cubic splines in an environment with obstacles considering not only
velocity and acceleration but also jerk constraints; the study is simulated on a six degrees of freedom
humanoid robot arm model and always finds a solution successfully if there is a feasible one.