Optimal task allocation in multi-human multi-robot interaction

Abstract

Multi-human multi-robot interaction is a complex system in which robots, e.g., unmanned aerial vehicles, may share information with a group of human operators to perform geographically-dispersed priority-based tasks within a specified time. In this complex system, the key is to optimally allocate tasks comprising of high-risk and low-risk information at multiple-levels in order to maximize effectiveness of the entire system given the limited resources. A multi-level programming model is developed in which an agent allocates information received from multiple robots to multiple team leaders who in turn distribute information to operators within their teams. The objective of the agent is to optimally allocate tasks to multiple team leaders to maximize the overall system performance and to minimize the processing cost and time while considering human factors. The developed model is solved using backward induction and details are presented in reverse time sequence. If human factors are included along with the productivity metrics then the performance of the multi-human multi-robot interaction systems can be improved.

On a human–robot workplace design and task allocation system

“…This enables the integration of new criteria, based on the user requirements and specifications. The proposed method considers multiple Chen et al (2014) and Malvankar-Mehta and Mehta (2015), the focus is rather given on maximising the overall system performance and minimising the processing cost and time. Rough simulation of HR tasks for Figure 11.…”

Smart Collaborative Systems for Enabling Flexible and Ergonomic Work Practices [Industry Activities]

“…The decision-making algorithms are often based on a multiple-criteria approach using a cost function, such as in [25], and use Markov decisions to determine the best execution plan [26]. Other allocation algorithms have been proposed to extend the task-assignment scheme to the multihuman-multirobot context [27]. The authors in [26] and [27] also took ergonomics into consideration when developing a task-allocation scheme.…”

Adaptive Workload Allocation for Multi-Human Multi-Robot Teams for Independent and Homogeneous Tasks

“…Task allocation with unknown robot capabilities have also been studied in [21]. Optimal task allocation with multi-humans in the loop has also been proposed in [22], where task allocation is performed over multiple-levels (group and individual) comprising of high-risk and low-risk information in order to max-imize effectiveness of the entire system minimizing processing cost and time, considering human factors given limited resources. In market-based approaches for multi-agent task allocation, the team seeks to optimize an objective function based upon robots utilities for performing particular tasks [23], [24]; desirable features of these approaches include efficiency in satisfying the objective function, robustness and scalability of the system.…”