Title
Learning coupling terms for obstacle avoidance
Abstract
Autonomous manipulation in dynamic environments is important for robots to perform everyday tasks. For this, a manipulator should be capable of interpreting the environment and planning an appropriate movement. At least, two possible approaches exist for this in literature. Usually, a planning system is used to generate a complex movement plan that satisfies all constraints. Alternatively, a simple plan could be chosen and modified with sensory feedback to accommodate additional constraints by equipping the controller with features that remain dormant most of the time, except when specific situations arise. Dynamic Movement Primitives (DMPs) form a robust and versatile starting point for such a controller that can be modified online using a non-linear term, called the coupling term. This can prove to be a fast and reactive way of obstacle avoidance in a human-like fashion. We propose a method to learn this coupling term from human demonstrations starting with simple features and making it more robust to avoid a larger range of obstacles. We test the ability of our coupling term to model different kinds of obstacle avoidance behaviours in humans and use this learnt coupling term to avoid obstacles in a reactive manner. This line of research aims at pushing the boundary of reactive control strategies to more complex scenarios, such that complex and usually computationally more expensive planning methods can be avoided as much as possible.
Year
DOI
Venue
2014
10.1109/HUMANOIDS.2014.7041410
Humanoid Robots
Keywords
Field
DocType
collision avoidance,manipulators,planning (artificial intelligence),autonomous manipulation,coupling term learning,dynamic environments,dynamic movement primitives,manipulator,obstacle avoidance,planning methods,planning system,reactive control strategies,robots
Obstacle avoidance,Control theory,Coupling,Everyday tasks,Simulation,Computer science,Simple Features,Robot,Reactive control,Trajectory
Conference
ISSN
Citations 
PageRank 
2164-0572
4
0.42
References 
Authors
11
4
Name
Order
Citations
PageRank
Akshara Rai1178.00
Franziska Meier210713.52
Auke Jan Ijspeert33546282.93
Stefan Schaal46081530.10