Decentralized Gaussian Processes[arXiv22] | [Pioneers22] | [ICRA21-1]
The goal of this project is to decentralize the implementation of Gaussian processes (GPs) in multi-agent systems. Decentralized GP training of the hyper-parameters is performed with the alternating direction method of multipliers in closed-form. Numerous aggregation of GP experts techniques are decentralized with the use of iterative and consensus methods. A covariance-based nearest neighbor selection strategy is introduced to enable a subset of agents to perform predictions.
Keywords: Gaussian Processes, Decentralized Networks, Multi-Agent Systems, Distributed Optimization.
Prediction of Wireless Communication Performance[RAS21] | [ACC21] | [WUWNET19]
The intent of this project is to develop methodologies for the prediction of underwater acoustic (UWA) communication performance. The measurements are modeled by a non-stationary Gaussian random field with a deterministic mean structure and a stochastic random component. We formulate basis functions inpired by accoustic propagation models to identify a spatial trend. Covariance estimation is addressed with a multi-stage iterative training method that produces unbiased and robust results with nested models. Prediction of UWA communication performance is performed with universal kriging.
Keywords: Spatial Prediction, Marine Robotics, Autonomous Underwater Vehicles, Communication Performance.
Online Kinodynamic Motion Planning[CHAPTER22] | [CDC21] | [ACC20] | [TNNLS19] | [ACC19]
The aim of this project is to provide online and safe kinodynamic motion planning algorithms with completely unknown/uncertain dynamics, based on continuous-time Q-learning. We utilize integral reinforcement learning to develop tuning laws for the online approximation of the optimal cost and the optimal policy in continuous-time. We modify motion planning techniques to perform efficient online local re-planning by employing topological connectedness tools.
Keywords: Motion Planning, Reinforcement Learning, Optimal Control, Game Theory.
Anthropomorphic Robot Hands[ICRA21-2] | [HUMANOIDS19] | [FRONTIERS19] | [ICORR19]
This research project contributes to the development of a new class of anthropomorphic, adaptive robot hands. The robot hands can operate in unstructured environments and can achieve various grasping and in-hand manipulation actions with minimal number of actuators. The design is optimized according to the human hand characteristics as described in anthropometric studies. The fabrication procedure consists of 3D printing and deposition manufacturing techniques.
Keywords: Adaptive Robot Hands, Compliant Mechanisms, Dexterous Manipulation.
Prosthetic Hands[FRONTIERS21] | [IROS15]
This research project focuses on the design and development of anthropomorphic, underactuated, personalized robot hands of low cost and weight. Elastic joints were selected to introduce passive compliance in the hand's structure, to simplify the control problem, and to enhance the grasping capabilities. We devise various diﬀerential mechanisms to facilitate the execution of diﬀerent grasping postures and gestures.
Keywords: Prosthesis design, Differential Mechanisms, Robust Grasping.