New developments, innovations, and advancements in robotic technology are paving the way for intelligent robots to enable, support, and enhance the capabilities of human workers in manufacturing environments. We envision future industrial robot assistants that support workers in their tasks, advancing manufacturing quality and processes and increasing productivity. However, this requires new channels of fine-grained, fast and reliable communication. In this research we examined the communication required for human-robot collaboration in a vehicle door assembly scenario. We identified potential communicative gestures applicable to this scenario, implemented these gestures on a Barrett WAMTM1manipulator, and evaluated them in terms of human recognition rate and response time in a real-time interaction. Response time analysis reveals insights into the communicative structure of robot motions; namely, key short gesture segments include the bulk of the communicative information. These results will help us design more efficient and fluid task flow in human-robot interaction scenarios.

Nonverbal communication cues play an important role in human-human interaction and are expected to take a similar role in human-robot collaboration. In current industrial practice, human-robot turn-taking is explicitly human controlled, via a command channel such as switch or button. However, such a master-slave approach does not permit collaborative interaction, and requires the human to focus on both controlling the robot's behavior and on the task, thereby affecting overall performance. In this paper, implicit, nonverbal communication cues are examined as a non-explicit communication channel during a turn-taking task context. The aim of this study is to characterize the types and frequencies of nonverbal cues important to regulating turn taking during an assembly-task-type collaboration. This analysis will guide the selection of cues that can be expressed by the robot as implicit user inputs while human and robot complete a shared task.

Real-time estimates of environment dynamics play an important role in the design of controllers for stable interaction between robotic manipulators and unknown environments. The Hunt-Crossley (HC) dynamic contact model has been shown to be more consistent with the physics of contact, compared with the classical linear models, such as Kelvin-Voigt (KV). This paper experimentally evaluates the author's previously proposed single-stage identification method for real-time parameter estimation of HC nonlinear dynamic models. Experiments are performed on various dynamically distinct objects, including an elastic rubber ball, a piece of sponge, a polyvinyl chloride (PVC) phantom, and a PVC phantom with a hard inclusion. A set of mild conditions for guaranteed unbiased estimation of the proposed method is discussed and experimentally evaluated. Furthermore, this paper rigorously evaluates the performance of the proposed single-stage method and compares it with those of a double-stage method for the HC model and a recursive least squares method for the KV model and its variations in terms of convergence rate, the sensitivity to parameter initialization, and the sensitivity to the changes in environment dynamic properties.

In this paper, a powerful robust stability analysis technique is introduced and developed for teleoperation systems. The methodology is based on wave parameters and discusses absolute stability and potential instability using scattering and is originally used in microwave systems [1]. The proposed method provides suitable mathematical and visual aids to determine bounds or regions of passive environment impedances for which a potentially unstable system connected to any passive operator is stable, and vice-versa. Furthermore, a novel stability parameter is proposed to maximize the derivation of the above bounds or regions. This results in less conservative guaranteed stability conditions compared to the Llewellyn’s criterion; thus, achieving a better compromise between stability and performance. The proposed methodology allows for the design of bilateral control systems when such bounds are known or even when the operator or environment dynamics are active. The new robust stability analysis and Llewellyn’s criterion are numerically evaluated and compared with each other on two common teleoperation control architectures.

This paper proposes a novel framework for the analysis and design of linear teleoperation controllers that are robust to time-delay. The framework that is based upon the earlier work of the authors employs scattering parameters and reflection coefficients to guarantee absolute stability of the system under any amount of delays. The proposed framework that incorporates both stability and performance considerations is utilized to design two new delay-robust bilateral controllers and the stability and performance of these controllers are rigorously evaluated.

In this paper, we study the performance of various algorithms for fast online identification of environment impedance during robotic contact tasks. In particular, we evaluate and compare algorithms with regard to their convergence rate, computational complexity and sensitivity to noise for different environments using a single degree-of-freedom experimental setup. The results provide some guidelines for choosing an appropriate identification algorithm for a specific application.

Online estimates of unknown environment dynamics are used for the control of robotic contact tasks. The Hunt-Crossley nonlinear dynamic model of environments has been shown to be more consistent with the physics of contact, compared to the classical linear models, such as Kelvin-Voigt. This paper proposes a new method for online parameter estimation of Hunt-Crossley model and provides a mild set of conditions for guaranteed unbiased estimation. The rate and the sensitivity of convergence to parameter initialization and system parameter changes are numerically evaluated and compared for both the proposed method and an existing 2-stage identification method.