Title
Proprioceptive sensing for autonomous self-righting on unknown sloped planar surfaces.
Abstract
Robots that operate in dynamic, unknown environments occasionally require error recovery methods to return to a preferred orientation for mobility (i.e. self-righting), thus preventing mission failure and enabling asset recovery. In this paper, we reduce to practice our previously developed framework for determining self-righting solutions for generic robots on sloped planar surfaces. We begin by briefly reviewing our framework. We then describe the development of a modular robot for examining the effectiveness of our framework. This robot utilizes only joint encoders and an inertial measurement unit (IMU) for sensing. Next, we test the fidelity of our sensors by comparing commanded values, sensor data, and ground truth as given by a Vicon motion capture sensor environment, yielding a baseline margin of error. We utilize this data to explore the robot's ability to determine unknown ground angles using only proprioceptive sensors in combination with a conformation space map, which is pre-computed using our framework. We then investigate the robot's ability to develop its own conformation space map experimentally, and compare it to the pre-computed map. Finally, we demonstrate the robot's ability to self-right on various ground angles using 1, 2, and 3 degrees of freedom.
Year
DOI
Venue
2013
10.1109/ROSE.2013.6698436
ROSE
Keywords
Field
DocType
angular measurement,inertial systems,mechanoception,mobile robots,position control,self-adjusting systems,IMU,Vicon motion capture sensor environment,asset recovery,autonomous self-righting,conformation space map,dynamic unknown environments,error recovery method,generic robots,inertial measurement unit,joint encoders,mission failure,modular robot,proprioceptive sensing,robot mobility,robot orientation,sensor data,unknown ground angle determination,unknown sloped planar surfaces
Robot control,Computer vision,Motion capture,Simulation,Computer science,Ground truth,Inertial measurement unit,Artificial intelligence,Modular design,Robot,Margin of error,Mobile robot
Conference
Citations 
PageRank 
References 
1
0.39
7
Authors
3
Name
Order
Citations
PageRank
Jason Collins1152.64
Chad C. Kessens2102.30
Stephen Biggs381.74