Integrated Astronaut Control System for EVA

Penn State Mars Society

RASC-AL 2003

Problem Statement

Future of space exploration: manned missions to Mars

Exploration issuesLong time delay from Earth

EVAs far from home base

These issues never previously encountered fully

Exploration Applications

Soil and rock samples

Surveying the Martian terrain

Scientific observation

Spacesuit

Bulkiness makes mobility difficult

Lack of flexibility

GlovesHand fatigue

Difficult to grasp objects

Solution: Rover accompanies astronaut

Rover Assisted Exploration

Rovers: tried and true Martian explorers

Useful toolkit for astronauts on EVAs

On-site rover control by astronauts

Variety of rover control systemsJoystick

Trackball

VR glove

Rover Control

Past: Control from EarthSupercomputers

Delay due to transmission over large distance

Joystick control

Future: On-site control by astronautJoystick and trackball not practical

VR Glove

Design Requirements

Fine-tuned control

No overlap between commands

Efficient response to commands

Simplicity and ease of training

Transmission efficiency (range and power)

Multitasking

Virtual Reality Gloves

Simulates the environment for practical purposesFlight training

Education

CapabilitiesSix degrees of freedom

Many more states than conventional controllers

Feedback Data

Integration into the Spacesuit

Characteristics:Mobility & Flexibility

Robust Function

Simple & Reliable

VR Glove is smallLightweight

Thin fibers

Best Place to Install:Max. sensitivity to hand motions

Between first and second layers

Our Solution

5DT Data Glove

ActivMedia Pioneer 2-AT rover

SmileCam camera

Steering and camera control by VR glove

Project Timeline

Gesture Control System

Data Input and Filtering

Gesture Recognition

State Selection

Device-Specific Output

Data Input and Filtering

Independent Input and Filter per hand

Raw glove data calibrated to user's range of motion

Exponential filter to smooth noisy dataMuscle Twinges

Cardiovascular pulses

Gesture Recognition

Hand sensor readings7.2e16 possible combinations!

Effect of finger dependencies with imprecise control: Not this many are realistic

Continuous Control: Mealy Model

Discrete Control: Moore Model

Hybrid Control

State Selection

Each hand operates independently

Certain states locked out to other hand

Root state allows external operation

Device-Specific Output

Translates gesture state into reasonable device output

Models exist for pan/tilt cameras, motion bases, and external microcontrollers

Player/Stage

Player: Robot device serverAbstracts device specifics from control class

Designed for networked operation from any language that supports TCP/IP

Stage: Simulator for Player controllersProvides simulated environment for controller development

Utilizes same binary interface as Player

Rover Navigation

Uses Player's PositionDevice class

Translates glove finger position and roll into rotational and translational velocities

Target Selection• Translates glove gestures to control PanTilt

device class• Manages selection of interesting targets

A Brief Demonstration

Testing

Obstacle Course requires:

1. Figure Eight2. Arcing Turn3. Reverse4. Slalom

Three Input Devices: Glove Joystick Trackball

Course Results

User B has more training than User A

Joystick is the fastest method

Trackball is significantly slower

Device User A User BGlove 02:15:00 01:32:00Joystick 01:30:00 01:12:00Trackball 04:27:00 04:32:00

Results Analysis

Results analyzed in the context of remote operations

Joystick is faster, but the glove has other advantages

Device Course Time Ease of Use Versatility Size / Weight Integration Total ScoreGlove 7 8 8 10 10 43Joystick 9 8 3 3 2 25Trackball 1 1 3 9 8 22

Future Developments

Touch Sensors

Force Feedback

More useful user feedback

Menuing

Sounds

Force Feedback

Autonomy in Tracking and Navigation

Questions