IEEE Robotics & Automation Magazine - December 2018 - 70

OTHex State
LBR-iiwa State
Gripper State
Operator Input
Environment Info
Grasping Point

Task Planner

Trajectory
Generator
FSM

Grippers cmd
OTHex Trajectory
LBR-iiwa Trajectory
Current State

(a)
Entry:

Both Manipulators Are
at Their Home Position

Grippers Closed
S3: Cooperative
Manipulation

S1: Take Off and
Approach to the Object

Task Achieved

Grasping Position

S4: Releasing

this case, even if the proposed path
planner relies on model inversion, the
sensitivity to parameter uncertainty
and disturbance is mitigated via a disturbance observer, the compliant
control of both manipulators, and
mechanical compliance. This renders
the full system reasonably robust to
parameter uncertainties (see [15] for
details on the OTHex side). In the
decentralized modality, such as the
leader-follower approach, during
cooperative manipulation the GM
manipulates the object, and the flying
manipulator assists the GM, following
its lead and producing additional
upward force on the bar.

Teleoperated MAGMaS
On the other end of the autonomy spectrum, the bilateral teleoperation approach
S5: Homing and Landing
can be used to cope with an unknown
environment and uncertainties and also
The Manipulation Task
facilitate completion of complex tasks.
Exit:
Is Completed
This is useful in scenarios like USAR,
(b)
where MAGMaS must work in a partially
or even completely unknown environment. In the bilateral teleoperation
Figure 3. (a) The task planner inputs and outputs for a cooperative manipulation task
performed by a Tele-MAGMaS. (b) The simple FSM implemented in our task planner.
approach, skilled human operators drive
the system in a precise and safe way while
being provided with force feedback to
increase situational awareness on the remote side.
In fact, in the bilateral teleoperation approach, the human
p∈ 6
intelligence
performs the task planning with the help of visual
Operator
Tele-MAGMaS
and haptic feedback. If direct visual feedback is not possible,
3
fhap = fM + fo ∈
cameras can be mounted on the robots. In the noncooperative
parts of the task (S1, S2, and S5), the human operator drives
Figure 4. An illustration of the bilateral teleoperation scheme,
the robots; in the cooperative part ^S3h, the operator comwith the operator commanding the position P and receiving a
mands the bar while the robots cooperatively manipulate the
force feedback fhap rendering the system inertia and proximity
to obstacles.
bar to perform the human command. Gripper and state
changes are manually triggered by the operator. In this case,
Fully Autonomous MAGMaS
the human intelligence decides how to move the robots, what
The fully autonomous operation mode of the MAGMaS is the suitable contact points are, how to move the bar, and along
targeted for use when the system evolves in a well-struc- which path the robots should return to their home position.
tured environment that is known in detail. It relies on two The desired object pose and current object state are sent to the
key components, a trajectory planner and a finite-state object pose controller, which computes low-level inputs for the
machine (FSM), that together make up the task planner robots' controller.
[Figure 3(a)]. The FSM is detailed in Figure 3(b) and defines
The operator is provided with a haptic feedback, fhap (Figthe policy used by the task planner to generate the robot ure 4), which depends both on the inertia of the whole sysmotion trajectories and trigger the grippers actions, based tem, through fM, and on a repulsive viscoelastic virtual force,
on robot and environmental information and the operator.
fo, generated to let the operator feel the obstacles in the enviThe autonomous cooperative manipulation phase (S3) can ronment. This yields
be implemented in a centralized or decentralized way. In cenfhap = fM + fO
tralized cooperative manipulation, both robots receive comfM = M x xp
mands based on the position of the manipulated object. A
detailed description of this approach can be found in [14]. In
fO = K P d min + K D do min,
Grippers Open

S2: Grasping

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IEEE Robotics & Automation Magazine - December 2018

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