  Remote-controlled humanoid robots can revolutionize manufacturing,
construction, and healthcare industries by performing complex or dangerous
manual tasks traditionally done by humans. We refer to these behaviors as
Dynamic Loco-Manipulation (DLM). To successfully complete these tasks, humans
control the position of their bodies and contact forces at their hands. To
enable similar whole-body control in humanoids, we introduce loco-manipulation
retargeting strategies with switched position and force control modes in a
bilateral teleoperation framework. Our proposed locomotion mappings use the
pitch and yaw of the operator's torso to control robot position or
acceleration. The manipulation retargeting maps the operator's arm movements to
the robot's arms for joint-position or impedance control of the end-effector. A
Human-Machine Interface captures the teleoperator's motion and provides haptic
feedback to their torso, enhancing their awareness of the robot's interactions
with the environment. In this paper, we demonstrate two forms of DLM. First, we
show the robot slotting heavy boxes (5-10.5 kg), weighing up to 83% of the
robot's weight, into desired positions. Second, we show human-robot
collaboration for carrying an object, where the robot and teleoperator take on
leader and follower roles.
