Paper Info
Title
Data-Driven Discrete Planning For Targeted Hopping Of Compliantly Actuated Robotic Legs
Abstract
Motion planning for fast locomotion of compliantly actuated robotic legs is generally considered to be a challenging issue, posing considerable real-time problems. This is at least the case if time-continuous trajectories need to be generated online. In this paper we take advantage of a simple controller structure, which reduces the motion planning to a discrete-time planning problem, in which only a small set of input parameters need to be determined for each step. We show that for a planar leg with serial elastic actuation, hopping on a ground with stairs of irregular length and height can be planned online, based on a parameter mapping which has been learned in a data-driven manner by performing hopping trials with an adaptive exploration algorithm to evenly sample the parameter space. Experiments on a planar hopping leg prototype validate the approach.
Year
DOI
Venue
2018
10.1109/IROS.2018.8593819
2018 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS)
Field
DocType
ISSN
Motion planning,Control theory,Data-driven,Computer science,Simulation,Control engineering,Planar,Parameter space,Small set,Stairs
Conference
2153-0858
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Daniel Seidel100.68
Dominic Lakatos2478.03
Alin Albu-Schaffer32831262.17