In this ongoing study, we are exploring the suitability of a novel technique based on the estimation of muscle synergies to control a hand prosthesis. The objective of the study is to predict thirteen distinct hand grasp movements using EMG data. The method relies on projecting the EMG data using a basis derived via analysis of the muscle synergies. Five healthy subjects performed a set of thirteen distinct hand grasp movements while sEMG data from seven muscles have been recorded.

With electronic devices increasingly interacting with each other and with the physical world around them, device behavior is becoming more and more like human behavior, namely reliant on experiences and not just data. Hence, there’s a disconnect between how most devices have been engineered and what what practitioners are expecting them to do, and because of this fact, there’s also a disconnect between the common cyber-security protections that protect data and some of the desirable proofs and verifications that can be highly valuable to cyber-physical devices.

Recent years have seen a rapid influx of autonomy in critical agricultural sectors. Many applications of autonomy in agriculture are restricted to passive data collection and remote monitoring. At the same time, there are fundamentally important problems that remain relatively untreated by recent thrusts in autonomous precision agriculture. This project lies precisely at the intersection of important theoretical challenges in robotic planning and perception, and critical frontiers in agriculture.

Large scale deployment of connected and automated vehicles is impeded by significant technical and scientific gaps, especially when it comes to achieving real-time and high accuracy situational awareness for cooperating vehicles. This CAREER project aims at closing these gaps through developing fundamental information networking methodologies for coordinated control of automated systems. These methodologies are based on the innovative concept of modeled knowledge propagation. The approach is to utilize the novel concepts of model communication and its derived multi-resolution networking.

Energy storage and power distribution comprise an integral part of the engineered systems that play critical roles in people’s everyday lives, including transportation, utility, health, and security. However, in today’s cyber-physical platforms, the generation, storage, allocation, and distribution of energy among modules is often managed in a haphazard and rigid manner that is fixed at the system design stage.

Overview: The goal of this project is to devise computational methods for the optimal coordination of autonomous mobility-on-demand (AMoD) systems, with a central focus on accounting for the couplings between the power and transportation networks. AMoD is a rapidly developing mode of transportation wherein self-driving, electric vehicles transport passengers on demand in a given environment (similar to an Uber system, but with self-driving, electric vehicles).

Cyber-physical systems (CPS), particularly those within the safety-critical domain, must continually ensure that their requirements are being satisfied. To support online requirements satisfaction, a CPS can be modeled with self-adaptive characteristics (SA-CPS) to enable the system to self-reconfigure as uncertainty manifests in both the environment and the system itself.