Handover Control for Human-Robot and Robot-Robot Collaboration

Abstract

Modern scenarios in robotics involve human-robot collaboration or robot-robot cooperation in unstructured environments. In human-robot collaboration, the objective is to relieve humans from repetitive and wearing tasks. This is the case of a retail store, where the robot could help a clerk to refill a shelf or an elderly customer to pick an item from an uncomfortable location. In robot-robot cooperation, automated logistics scenarios, such as warehouses, distribution centers and supermarkets, often require repetitive and sequential pick and place tasks that can be executed more efficiently by exchanging objects between robots, provided that they are endowed with object handover ability. Use of a robot for passing objects is justified only if the handover operation is sufficiently intuitive for the involved humans, fluid and natural, with a speed comparable to that typical of a human-human object exchange. The approach proposed in this paper strongly relies on visual and haptic perception combined with suitable algorithms for controlling both robot motion, to allow the robot to adapt to human behavior, and grip force, to ensure a safe handover. The control strategy combines model-based reactive control methods with an event-driven state machine encoding a human-inspired behavior during a handover task, which involves both linear and torsional loads, without requiring explicit learning from human demonstration. Experiments in a supermarket-like environment with humans and robots communicating only through haptic cues demonstrate the relevance of force/tactile feedback in accomplishing handover operations in a collaborative task.

Assistance to Older Adults with Comfortable Robot-to-Human Handovers

“…Here, giver and receiver must analyse the exchange of gripping forces to confirm the correct transfer of the object. Indeed, studies highlights the importance of this haptic perception between a human and a robot [19]. These grip forces tells if the other individual whether s/he intends to let go or take the object and also whether s/he is holding it properly.…”

Trends of Human-Robot Collaboration in Industry Contexts: Handover, Learning, and Metrics

“…Several recent works have already developed partial solutions regarding the humanrobot object handover procedure [132][133][134], some of which are inspired by human strategies [83,103,135,136]. However, none of them provides a generic solution for a human adaptive system, where the exchange of objects occurs fluently, similarly to what happens between two humans, for the robot to become a much more reliable and useful machine.…”

Model Predictive Control for Fluid Human-to-Robot Handovers

“…Finally, during the physical handover phase, i.e., from the first contact of the receiver's hand on the object till the release of the object, force feedback can be used to decide when to release the object (robot-to-human) or when to grasp the object (human-to-robot) [8]. However, the raw force/torque sensor readings are often noisy and hard to interpret directly [9].…”