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Transporting objects using quadrotors with cables has been widely studied in the literature. However, most of those approaches assume that the cables are previously attached to the load by human intervention. In tasks where multiple objects need to be moved, the efficiency of the robotic system is constrained by the requirement of manual labor. Our approach uses a non-stretchable cable connected to two quadrotors, which we call the catenary robot, that fully automates the transportation task. Using the cable, we can roll and drag the cuboid object (box) on planar surfaces. Depending on the surface type, we choose the proper action, dragging for low friction, and rolling for high friction. Therefore, the transportation process does not require any human intervention as we use the cable to interact with the box without requiring fastening. We validate our control design in simulation and with actual robots, where we show them rolling and dragging boxes to track desired trajectories.
We present a novel method enabling robots to quickly learn to manipulate objects by leveraging a motion planner to generate expert training trajectories from a small amount of human-labeled data. In contrast to the traditional sense-plan-act cycle, w
Transporting objects using aerial robots has been widely studied in the literature. Still, those approaches always assume that the connection between the quadrotor and the load is made in a previous stage. However, that previous stage usually require
This paper presents an approach to in-hand manipulation planning that exploits the mechanics of alternating sticking contact. Particularly, we consider the problem of manipulating a grasped object using external pushes for which the pusher sticks to
Consider the problem of planning collision-free motion of $n$ objects in the plane movable through contact with a robot that can autonomously translate in the plane and that can move a maximum of $m leq n$ objects simultaneously. This represents the
We present a user-friendly interface to teleoperate a soft robot manipulator in a complex environment. Key components of the system include a manipulator with a grasping end-effector that grows via tip eversion, gesture-based control, and haptic disp