Research

The first demonstration of an automated driving system in a rural road environment has been successively finished. This demo was a part of the AVA (Autonomous Vehicles for All) project. Our UIUC team has collaborated with the Texas A&M team to prepare this demo.

Several studies have proved that autonomous vehicles (AVs) can positively impact the life in future, especially as the market penetration rate of the AV in the market reaches a certain percentage. Therefore, the expansion of AVs in the market has become an important issue. Driving comfort is among the crucial factors that can contribute to the public acceptance of AVs. Only a few studies, however, took the comfort states of occupants in AVs into account when designing algorithms for AV operations. Hence, this study aims to develop a model to estimate passengers’ comfort states in AVs based on facial expressions recognition. The proposed model can further improve AV’s path planning based on the occupant’s comfort state. The present study also offers an experimental study to assess the model’s capability in effectively estimating passengers’ comfort states. The experiments resulted in the identification of the factors that AV developers can utilize to design more comfortable AVs in the future.

This paper presents a trajectory generation approach for car-following behavior in response to a lane-changing vehicle. The approach is based on a quadratic B´ezier curve created on a time-space diagram. According to the properties of the curve on the time-space diagram, we propose a methodology for the following vehicle to adapt to sudden interruption of its leader (i.e.,lane-changing vehicle) considering driving comfort and its impact on traffic. Based on the derivation of the acceleration term, we late a trajectory generation algorithm for safe car-following behavior. In detail, the formulation factors into initial braking and speed reduction along the curve. The results show that when a lane-changing trajectory is provided, the formulation not only outputs a safe trajectory curve but also adjusts it depending on the preferred driving pattern.

Sediment has a significant impact on social, economic, and environmental systems. With the
need for an effective sediment management and monitoring systems growing more important, a method for precisely and reproducibly obtaining sediment samples that represent the actual environment is essential for water resource management and researchers across aquatic domains (such as lakes, rivers, reservoirs, mine drainage ponds, and wastewater lagoons). To meet this need, robotic approaches for sediment sampling have been introduced. However, they are not tailored to a sediment sampling method and do not focus on the quality of the sediment sample. In this paper, we introduce an uncrewed sediment sampling system based on the unmanned surface vehicle (USV) and underwater sediment sampler (USS) to collect sediment samples and with the ability to comprehensively study sample quality from surface-water environments. The main objective of the USV is to carry the USS to the desired sampling area and then maintain its position while launching the USS to the bottom of the body of water and sampling the sediment.

Dr. Min and I visited Arequipa and Majes, Peru for the evaluation of an uncrewed remote underwater sediment sampling system in December 2021. We teamed up with people from the National University of Saint Augustine including Dr. Mauricio Postigo-Malaga and Dr. Edgar Gonzales Zenteno. Our target site for the field experiment was the artificial lagoon in Mejes, Peru. Our team could evaluate this system even in a different country. This trip was invaluable and I could learn and experience many things.

Supplementary video material for IEEE Journal of Oceanic Engineering paper.

Title: Evaluation of Sampling Methods for Robotic Sediment Sampling Systems

Authors: Jun Han Bae, Wonse Jo, Jee Hwan Park, Richard M. Voyles, Sara K. McMillan, and Byung-Cheol Min

This is the supplementary video for OCEANS' 2019 conference.

This is a video presentation for the paper: "Development of an Unmanned Surface Vehicle for Remote Sediment Sampling with a Van Veen Grab Sampler," in OCEANS Seattle '19, by Jun Han Bae, Shaocheng Luo, Shyam Sundar Kannan, Yogang Singh, Bumjoo Lee, Richard M. Voyles, Mauricio Postigo-Malaga, Edgar Gonzales Zenteno, Lizbeth Paredes Aguilar, and Byung-Cheol Min.

Rendezvous control of multiple robots without losing network connectivity has important implications in multi-robot system including formation control, coordinated task assignments and cooperative robotic missions. This paper introduces a new coordinate-free, bearing-based algorithm to enable rendezvous of distributed mobile robots at any designated leader robot node using hierarchical tracking of wireless network topology. An assumption is made that the robot can only sense and communicate with their neighbors (i.e., local sensing). The proposed approach preserves connectivity during the rendezvous task, adapts to dynamic changes in the network topology (e.g., losing or re-gaining a communication link), and is tolerant of mobility faults in the robots. We theoretically analyze the proposed algorithm and experimentally demonstrate the approach through simulations and extensive f ield experiments. The results indicate that the method is effective in a variety of realistic scenarios in which the robots are distributed in a cluttered environment.

This paper presents a novel collective coverage control strategy for robots to achieve effective coverage over a large-scale spill. The proposed idea is based on the divide and conquers approach that partitions a large irregular spill in the workspace into a number of smaller zones and let the robot team cover each packing zone sequentially. Ultimately, the robot team can cover the entire area. For an effective coverage operation in diverse and dynamic environments, we propose a pivot-based control strategy performed by a pivot robot and multiple planet robots. The pivot robot is located at the center of the area to be covered and serves as a lighthouse to all the working robots denoted as planet robots exploring the area. By doing so, the planet robots do not require a global coordinate system nor massive communication between robots for their coordination, ultimately enabling an efficient, adaptive, scalable, and fault-tolerant coverage operation. The proposed strategy is validated through extensive simulation experiments with different packing shapes and different numbers of robots.

Recently, the advent of 3D printers has enabled people to produce a lot of inexpensive and obtainable prosthetics. In addition to that, various sensors have also been developed and used to give intelligent functions to prosthetics. However, there may be cases where the number of sensors attached to the prosthetics should be limited due to cost, limited space, or power issues as the number of sensors increases. Therefore, in this paper, we provide a design guideline that could be used to determine the ideal sensor locations, particularly when the number of sensors is limited by finding out the locations of the high contact areas where the prosthetic hand touches the object. To this end, we experiment with a popular prosthetic hand-made using a 3D printer. The prosthetic hand with gloves is used to touch two different objects that are covered with black ink, and the area of ink transferred onto the gloves is measured by image processing. Experiments are conducted ten times on the same object to obtain statistical results, and as a result, we show the most contact areas with the objects and present the guidelines.