Related papers: Modeling Human-Human Collaboration: A Connection B…
Human movement has been studied for decades and dynamic laws of motion that are common to all humans have been derived. Yet, every individual moves differently from everyone else (faster/slower, harder/smoother etc). We propose here an…
Collaborative robots can relief human operators from excessive efforts during payload lifting activities. Modelling the human partner allows the design of safe and efficient collaborative strategies. In this paper, we present a control…
Human behavior modeling is important for the design and implementation of human-automation interactive control systems. In this context, human behavior refers to a human's control input to systems. We propose a novel method for human…
This paper considers the leader-follower tracking control problem for linear interconnected systems with undirected topology and linear dynamic coupling. Interactions between the systems are treated as linear dynamic uncertainty and are…
We describe a shared control methodology that can, without knowledge of the task, be used to improve a human's control of a dynamic system, be used as a training mechanism, and be used in conjunction with Imitation Learning to generate…
Recent progress in human-robot collaboration makes fast and fluid interactions possible, even when human observations are partial and occluded. Methods like Interaction Probabilistic Movement Primitives (ProMP) model human trajectories…
Effective human-robot collaboration requires informed anticipation. The robot must anticipate the human's actions, but also react quickly and intuitively when its predictions are wrong. The robot must plan its actions to account for the…
This paper explores cooperative trajectory planning approaches within the context of human-machine shared control. In shared control research, it is typically assumed that the human and the automation use the same reference trajectory to…
We propose a hybrid model predictive control algorithm, consensus complementarity control (C3), for systems that make and break contact with their environment. Many state-of-the-art controllers for tasks which require initiating contact…
For successful goal-directed human-robot interaction, the robot should adapt to the intentions and actions of the collaborating human. This can be supported by musculoskeletal or data-driven human models, where the former are limited to…
We present Intermittent Control (IC) models as a candidate framework for modelling human input movements in Human--Computer Interaction (HCI). IC differs from continuous control in that users are not assumed to use feedback to adjust their…
Human interaction involves very sophisticated non-verbal communication skills like understanding the goals and actions of others and coordinating our own actions accordingly. Neuroscience refers to this mechanism as motor resonance, in the…
An important factor in developing control models for human-robot collaboration is how acceptable they are to their human partners. One such method for creating acceptable control models is to attempt to mimic human-like behaviour in robots…
We synthesize shared control protocols subject to probabilistic temporal logic specifications. More specifically, we develop a framework in which a human and an autonomy protocol can issue commands to carry out a certain task. We blend…
This paper studies a class of consensus dynamics where the interactions between agents are affected by a time-varying unknown scaling factor. This situation is encountered in the control of robotic fleets over a wireless network or in…
This paper investigates the cooperative control of multiple unmanned and manned vehicles via an output containment control approach for heterogeneous discrete-time multiagent systems. The unmanned vehicles act as leading vehicles to guide…
This paper proposes a consensus controller for multi-agent systems that can guarantee the agents' safety. The controller, built with the idea of output prediction and the Newton-Raphson method, achieves consensus for a class of…
Future intelligent system will involve very various types of artificial agents, such as mobile robots, smart home infrastructure or personal devices, which share data and collaborate with each other to execute certain tasks.Designing an…
Designing effective rehabilitation strategies for upper extremities, particularly hands and fingers, warrants the need for a computational model of human motor learning. The presence of large degrees of freedom (DoFs) available in these…
Humans show specialized strategies for efficient collaboration. Transferring similar strategies to humanoid robots can improve their capability to interact with other agents, leading the way to complex collaborative scenarios with multiple…