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This manuscript introduces an object deformability-agnostic framework forco-carrying tasks that are shared between a person and multiple robots. Ourapproach allows the full control of the co-carrying trajectories by the personwhile sharing the load with multiple robots depending on the size and theweight of the object. This is achieved by merging the haptic informationtransferred through the object and the human motion information obtained from amotion capture system. One important advantage of the framework is that nostrict internal communication is required between the robots, regardless of theobject size and deformation characteristics. We validate the framework with twochallenging real-world scenarios: co-transportation of a wooden rigid closetand a bulky box on top of forklift moving straps, with the lattercharacterizing deformable objects. In order to evaluate the generalizability ofthe proposed framework, a heterogenous team of two mobile manipulators thatconsist of an Omni-directional mobile base and a collaborative robotic arm withdifferent DoFs is chosen for the experiments. The qualitative comparisonbetween our controller and the baseline controller (i.e., an admittancecontroller) during these experiments demonstrated the effectiveness of theproposed framework especially when co-carrying deformable objects. Furthermore,we believe that the performance of our framework during the experiment with thelifting straps offers a promising solution for the co-transportation of bulkyand ungraspable objects.

Carrying the uncarriable: a deformation-agnostic and human-cooperative framework for unwieldy objects using multiple robots