Semi-autonomous control

Semi-autonomous control

SEMI-AUTONOMOUS Another line of research in teleoperation is semi-autonomous control, often
CONTROL called supervisory control, where the remote is given an instruction or por-
SUPERVISORY CONTROL tion of a task that it can safely do on its own. There are two flavors of
semi-autonomous control: continuous assistance, or shared control, and control
trading.
SHARED CONTROL In continuous assistance systems, the teleoperator and remote share control.
The teleoperator can either delegate a task for the robot to do or can
do it via direct control. If the teleoperator delegates the task to the robot,
the human must still monitor to make sure that nothing goes wrong. This is
particularly useful for teleoperating robot arms in space. The operator can
relax (relatively) while the robot arm moves into the specified position near
a panel, staying on alert in case something goes wrong. Then the operator
can take over and perform the actions which require hand-eye coordination.
Shared control helps the operator avoid cognitive fatigue by delegating boring,
repetitive control actions to the robot. It also exploits the ability of a

human to perform delicate operations. However, it still requires a high communication
bandwidth.
An alternative approach is CONTROL TRADING control trading,where the human initiates an action
for the robot to complete autonomously. The human only interacts with
the robot to give it a new command or to interrupt it and change its orders.
The overall scheme is very much like a parent giving a 10-year old child a
task to do. The parent knows what the child is able to do autonomously
(e.g., clean their room). They have a common definition (clean room means
go to the bedroom, make the bed, and empty the wastebaskets). The parent
doesn’t care about the details of how the child cleans the room (e.g., whether
the wastebasket is emptied before the bed is made or vice versa). Control
trading assumes that the robot is capable of autonomously accomplishing
certain tasks without sharing control. The advantage is that, in theory, the
local operator can give a robot a task to do, then turn attention to another
robot and delegate a task to it, etc. A single operator could control multiple
robots because they would not require even casual monitoring while they
were performing a task. Supervisory control also reduces the demand on
bandwidth and problems with communication delays. Data such as video
images need to be transferred only when the local is configuring the remote
for a new task, not all the time. Likewise, since the operator is not involved
in directly controlling the robot, a 2.5 minute delay in communication is irrelevant;
the robot either wrecked itself or it didn’t. Unfortunately, control
trading assumes that robots have actions that they can performrobustly even
in unexpected situations; this may or may not be true. Which brings us back
to the need for artificial intelligence.
Sojourner exhibited both flavors of supervisory control. It was primarily
programmed for traded control, where the geologists could click on a rock
and Sojourner would autonomously navigate close to it, avoiding rocks, etc.
However, some JPL employees noted that the geologists tended to prefer to
use shared control, watching every movement. A difficulty with most forms
of shared control is that it is assumed that the human is smarter than the
robot. This may be true, but the remote may have better sensor viewpoints
and reaction times.