Symbolic motion planning for robots is the process of specifying and planning robot tasks in
a discrete space, then carrying them out in a continuous space in a manner that preserves …

In this paper, we develop a Bayesian inference model for the degree of human trust in
multiple mobile robots. A linear model for robot performance in navigation and perception is …

This book aims to present new developments in control and decision-making theory in the
field of human–robot interaction (HRI). Despite advances in robotics, sensing, and …

Trust between team members is an essential requirement for any successful cooperation.
Thus, engendering and maintaining the fellow team members' trust becomes a central …

In this chapter, we investigate the collaboration between multi-human networks and swarm
networks. We focus on planar motion of a network of mobile swarm clusters, where each …

The main objective of tracking model predictive control is to stabilize the plant satisfying the
constraints and steering the tracking error, that is, the difference between the reference and …

Trust between team members is an essential requirement for any successful cooperation.
Thus, engendering and maintaining the fellow team members' trust becomes a central …

Using the context of human-supervised object collection tasks, we explore policies for a
robot to seek assistance from a human supervisor and avoid loss of human trust in the robot …

This paper is on human-robot collaborative site inspection and target classification. We
consider the realistic case that human visual performance is imperfect (depending on the …

Due to the complexity of real-world deployments, a robot swarm is required to dynamically
respond to tasks such as tracking multiple vehicles and continuously searching for victims …