Panel 2: Accountability for the Actions of Robots

Transcript of the panel discussion at the 2018 Seattle University School of Law symposium “Singularity: AI and the Law” discussing human control and Artificial Intellegence learning. The panel participants are Ryan Calo, Howard Jay Chizeck, Elizabeth Joh, and Blake Hannaford

Evaluation of haptic guidance virtual fixtures and 3D visualization methods in telemanipulation—a user study

© 2019, The Author(s). This work presents a user-study evaluation of various visual and haptic feedback modes on a real telemanipulation platform. Of particular interest is the potential for haptic guidance virtual fixtures and 3D-mapping techniques to enhance efficiency and awareness in a simple teleoperated valve turn task. An RGB-Depth camera is used to gather real-time color and geometric data of the remote scene, and the operator is presented with either a monocular color video stream, a 3D-mapping voxel representation of the remote scene, or the ability to place a haptic guidance virtual fixture to help complete the telemanipulation task. The efficacy of the feedback modes is then explored experimentally through a user study, and the different modes are compared on the basis of objective and subjective metrics. Despite the simplistic task and numerous evaluation metrics, results show that the haptic virtual fixture resulted in significantly better collision avoidance compared to 3D visualization alone. Anticipated performance enhancements were also observed moving from 2D to 3D visualization. Remaining comparisons lead to exploratory inferences that inform future direction for focused and statistically significant studies

Continuous Operator Authentication for Teleoperated Systems Using Hidden Markov Models [post-print]

In this article, we present a novel approach for continuous operator authentication in teleoperated robotic processes based on Hidden Markov Models (HMM). While HMMs were originally developed and widely used in speech recognition, they have shown great performance in human motion and activity modeling. We make an analogy between human language and teleoperated robotic processes (i.e., words are analogous to a teleoperator\u27s gestures, sentences are analogous to the entire teleoperated task or process) and implement HMMs to model the teleoperated task. To test the continuous authentication performance of the proposed method, we conducted two sets of analyses. We built a virtual reality (VR) experimental environment using a commodity VR headset (HTC Vive) and haptic feedback enabled controller (Sensable PHANToM Omni) to simulate a real teleoperated task. An experimental study with 10 subjects was then conducted. We also performed simulated continuous operator authentication by using the JHU-ISI Gesture and Skill Assessment Working Set (JIGSAWS). The performance of the model was evaluated based on the continuous (real-time) operator authentication accuracy as well as resistance to a simulated impersonation attack. The results suggest that the proposed method is able to achieve 70% (VR experiment) and 81% (JIGSAWS dataset) continuous classification accuracy with as short as a 1-second sample window. It is also capable of detecting an impersonation attack in real-time

Static output-feedback stabilization of discrete-time Markovian jump linear systems: a system augmentation approach

This paper studies the static output-feedback (SOF) stabilization problem for discrete-time Markovian jump systems from a novel perspective. The closed-loop system is represented in a system augmentation form, in which input and gain-output matrices are separated. By virtue of the system augmentation, a novel necessary and sufficient condition for the existence of desired controllers is established in terms of a set of nonlinear matrix inequalities, which possess a monotonic structure for a linearized computation, and a convergent iteration algorithm is given to solve such inequalities. In addition, a special property of the feasible solutions enables one to further improve the solvability via a simple D-K type optimization on the initial values. An extension to mode-independent SOF stabilization is provided as well. Compared with some existing approaches to SOF synthesis, the proposed one has several advantages that make it specific for Markovian jump systems. The effectiveness and merit of the theoretical results are shown through some numerical example

Control of posture with FES systems

One of the major obstacles in restoration of functional FES supported standing in paraplegia is the lack of knowledge of a suitable control strategy. The main issue is how to integrate the purposeful actions of the non-paralysed upper body when interacting with the environment while standing, and the actions of the artificial FES control system supporting the paralyzed lower extremities. In this paper we provide a review of our approach to solving this question, which focuses on three inter-related areas: investigations of the basic mechanisms of functional postural responses in neurologically intact subjects; re-training of the residual sensory-motor activities of the upper body in paralyzed individuals; and development of closed-loop FES control systems for support of the paralyzed joints

Proceedings of the Fourth Annual Deep Brain Stimulation Think Tank: A Review of Emerging Issues and Technologies

This paper provides an overview of current progress in the technological advances and the use of deep brain stimulation (DBS) to treat neurological and neuropsychiatric disorders, as presented by participants of the Fourth Annual DBS Think Tank, which was convened in March 2016 in conjunction with the Center for Movement Disorders and Neurorestoration at the University of Florida, Gainesveille FL, USA. The Think Tank discussions first focused on policy and advocacy in DBS research and clinical practice, formation of registries, and issues involving the use of DBS in the treatment of Tourette Syndrome. Next, advances in the use of neuroimaging and electrochemical markers to enhance DBS specificity were addressed. Updates on ongoing use and developments of DBS for the treatment of Parkinson’s disease, essential tremor, Alzheimer’s disease, depression, post-traumatic stress disorder, obesity, addiction were presented, and progress toward innovation(s) in closed-loop applications were discussed. Each section of these proceedings provides updates and highlights of new information as presented at this year’s international Think Tank, with a view toward current and near future advancement of the field