Project Number 1: Design, Characterization, Modelling and Control of a Bio-inspired Fin Based Actuator Mechanism
This study introduces an innovative approach to modeling and characterization of a novel bio-inspired fin actuator mechanism for underwater applications. We employ a set of novel efficiency metrics to standardize performance comparisons across different platforms for both simulations and experiments. This fin mechanism offers a fresh perspective on underwater locomotion, particularly in addressing the trade-off between stability and maneuverability. This study contributes to advancing bio-inspired underwater actuator mechanisms, offering improved performance and adaptability.
Project Number 2: Feedback motion planning via sequential composition of random elliptical
funnels (FMP)
https://www.sciencedirect.com/science/article/pii/S0029801824020328
This study presents a novel feedback motion planning and control framework tailored for unmanned surface vehicles (USVs), validated through experiments on a physical USV platform. The framework utilizes sparse random neighborhood trees and a velocity command generator based on partial feedback linearization. The proposed trajectory-free, sampling-based feedback motion planning scheme is compatible with 2D polygonal map representations, enabling practical deployment in real-world environments for USVs. Moreover, the use of elliptical funnels enhances tree sparsity compared to circular funnels, thereby improving computational efficiency, reducing mode changes, and decreasing the total operation duration.
Project Number 3: Modeling, Simulation, and Control of a “Sensorless” Cable-Driven Robot
https://link.springer.com/chapter/10.1007/978-3-031-32322-5_16
This paper focuses on the modeling, simulation, control, and experimental validation of a planar cable-driven robot system that operates on the vertical (x-z) plane. Cable-driven robots have recently gained significant attention due to their successful commercial applications, such as spider cameras in large areas like stadiums. In this study, we model the robotic system as a planar dynamical system driven by visco-elastic tension elements (i.e., cables) attached between the four corners of the rectangular end-effector and corners of the workspace where the electric motors are connected. We assume that limited sensory information is available to the controller, such that we can only measure motor torque, and no direct information is available from the end-effector. This sensorless measurement assumption poses significant control challenges. We propose a novel control approach that adopts a parallel feedforward velocity and feedback force/torque control topology. The control inputs of the system are assumed to be the reference motor velocities, as we utilize industrial servo controllers with built-in velocity control capabilities. We model the motor dynamics as a first-order low-pass filter to account for the phase lag between the reference and actual motor commands. We first simulate the closed-loop system and test the effectiveness of the control policy under different unknown system parameters such as stiffness, damping, and motor lag. We then experimentally verify the topology on an actual experimental setup.We believe that these results are promising for future cable-driven robotic applications, especially for systems with limited sensory equipment.