Sampling-based finger gaits planning for multifingered robotic hand

Authors:
Jijie Xu;Tak-Kuen John Koo;Zexiang Li
Affiliations:
B. Thomas Golisano College of Computing and Information Sciences, Rochester Institute of Technology, Rochester, USA;Center for Embedded Software Systems, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China;Department of Electrical and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong, China
Venue:
Autonomous Robots
Year:
2010

Citing 5
Cited 3

The kinematics of contact and grasp

International Journal of Robotics Research
A Mathematical Introduction to Robotic Manipulation

A Mathematical Introduction to Robotic Manipulation
The theory of hybrid automata

LICS '96 Proceedings of the 11th Annual IEEE Symposium on Logic in Computer Science
Planning Algorithms

Planning Algorithms
Improving Motion-Planning Algorithms by Efficient Nearest-Neighbor Searching

IEEE Transactions on Robotics

Randomized multi-modal motion planning for a humanoid robot manipulation task

International Journal of Robotics Research
Contact-invariant optimization for hand manipulation

EUROSCA'12 Proceedings of the 11th ACM SIGGRAPH / Eurographics conference on Computer Animation
Contact-invariant optimization for hand manipulation

Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation

Quantified Score

Hi-index	0.00

Visualization

Abstract

To perform large scale or complicated manipulation tasks, a multi-fingered robotic hand sometimes has to sequentially adjust its grasp status to overcome constraints of the manipulation, such as workspace limits, force balance requirement, etc. Such a strategy of changing grasping status is called a finger gait, which exhibits strong hybrid characteristics due to the discontinuity caused by relocating limited fingers and the continuity caused by manipulating objects. This paper aims to explore the complicated finger gaits planning problem and provide a method for robotic hands to autonomously generate feasible finger gaits to accomplish given tasks. Based on the hybrid automaton formulation of a popular finger gaiting primitive, finger substitution, we formulate the finger gait planning problem into a classic motion planning problem with a hybrid configuration space. Inspired by the rapidly-exploring random tree (RRT) techniques, we develop a finger gait planner to quickly search for a feasible manipulation strategy with finger substitution primitives. To increase the search performance of the planner, we further develop a refined sampling strategy, a novel hybrid distance and an efficient exploring strategy with the consideration of the problem's hybrid nature. Finally, we use a representative numerical example to verify the validity of our problem formulation and the performance of the RRT based finger gait planner.