TaeWon Seo

Bio: TaeWon Seo is an academic researcher from Hanyang University. The author has contributed to research in topics: Robot & Mobile robot. The author has an hindex of 17, co-authored 165 publications receiving 1157 citations. Previous affiliations of TaeWon Seo include Yeungnam University & Carnegie Mellon University.

Tank-Like Module-Based Climbing Robot Using Passive Compliant Joints

Abstract: This paper proposes an underactuated modular climbing robot with flat dry elastomer adhesives. This robot is designed to achieve high speed, high payload, and dexterous motions that are typical drawbacks of previous climbing robots. Each module is designed as a tread-wheeled mechanism to simultaneously realize high speed and high adhesive force. Two modules are connected by compliant joints, which induce a positive preload on the front wheels resulting in stable climbing and high payload capacity. Compliant joints also help the robot to perform various transitions. An active tail is adopted to regulate the preload of the second module. Force transfer equations are derived and stable operating conditions are verified. The stiffness coefficients of the compliant joints and the active tail force are determined optimally to satisfy the constraints of stable operation. The prototype two-module robot achieves 6-cm/s speed and 500-g payload capacity on vertical surfaces. The abilities of flat surface locomotion, internal, external, and thin-wall transitions, and overcoming various sized obstacles are validated through experiment. The principle of joint compliance can be adopted in other climbing robots to enhance their stability and transition capability.

Six-Degree-of-Freedom Hovering Control of an Underwater Robotic Platform With Four Tilting Thrusters via Selective Switching Control

Abstract: We introduce a new underwater robotic platform with a tilting thruster mechanism for hovering motion. The tilting thruster mechanism can implement six-degree-of-freedom (DOF) motion with only four thrusters, but tilting motion makes the system nonlinear. We designed a selective switching controller in order to solve the nonlinear problem, and applied it to the robot system. The selective switching controller divides the six-DOF system into two three-DOF subsystems, and switches between subcontrollers according to the error in real time. Dynamic models of a robotic platform and a disturbance model of an attached manipulator are derived for the control design. Using simulation, the stability condition of control is determined, and the validity of the derived dynamic model of the robotic platform and manipulator is verified through comparison between simulation and experiment. A hovering experiment under a disturbance from the manipulator is performed to verify the robustness of the controller. The experimental results validate the successful hovering ability of the proposed robot.

Survey on Glass And Façade-Cleaning Robots: Climbing Mechanisms, Cleaning Methods, and Applications

Abstract: Cleaning dirty spaces is a very important task for human beings to maintain their quality of life. Recently, many high-rise buildings have been constructed, and their facades are easily contaminated by dust and pollution, especially in Asian countries such as China and Korea. Human workers are cleaning the facades, which are mostly made of glass, by hanging on to a gondola or rope, which entails spending a long time in midair, and this is dangerous work due to the risk of falling. To help humans avoid this dangerous and hard work, many researchers have tried to develop unmanned facade-cleaning robots; however, there are many issues to be solved before cleaning robots become efficient and popular. In this survey, we investigate and analyze robots used for cleaning building facades and glass. The robot are classified by types of climbing and attaching mechanisms, and their cleaning methods, mobility, and obstacle-overcoming performances are analyzed. In this paper, we also include for discussion some suggestions for making the robots more effective in real environments, and we expect that our work can provide reference to assist in the development of facade-cleaning robots for the real world.

Series of Multilinked Caterpillar Track-type Climbing Robots

Abstract: Climbing robots have been widely applied in many industries involving hard to access, dangerous, or hazardous environments to replace human workers. Climbing speed, payload capacity, the ability to overcome obstacles, and wall-to-wall transitioning are significant characteristics of climbing robots. Here, multilinked track wheel-type climbing robots are proposed to enhance these characteristics. The robots have been developed for five years in collaboration with three universities: Seoul National University, Carnegie Mellon University, and Yeungnam University. Four types of robots are presented for different applications with different surface attachment methods and mechanisms: MultiTank for indoor sites, Flexible caterpillar robot FCR and Combot for heavy industrial sites, and MultiTrack for high-rise buildings. The method of surface attachment is different for each robot and application, and the characteristics of the joints between links are designed as active or passive according to the requirement of a given robot. Conceptual design, practical design, and control issues of such climbing robot types are reported, and a proper choice of the attachment methods and joint type is essential for the successful multilink track wheel-type climbing robot for different surface materials, robot size, and computational costs.

Guidance And Control Of Ocean Vehicles

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Adaptive Neural Network Control of AUVs With Control Input Nonlinearities Using Reinforcement Learning

Abstract: In this paper, we investigate the trajectory tracking problem for a fully actuated autonomous underwater vehicle (AUV) that moves in the horizontal plane. External disturbances, control input nonlinearities and model uncertainties are considered in our control design. Based on the dynamics model derived in the discrete-time domain, two neural networks (NNs), including a critic and an action NN, are integrated into our adaptive control design. The critic NN is introduced to evaluate the long-time performance of the designed control in the current time step, and the action NN is used to compensate for the unknown dynamics. To eliminate the AUV’s control input nonlinearities, a compensation item is also designed in the adaptive control. Rigorous theoretical analysis is performed to prove the stability and performance of the proposed control law. Moreover, the robustness and effectiveness of the proposed control method are tested and validated through extensive numerical simulation results.

Soft wall-climbing robots

Abstract: Existing robots capable of climbing walls mostly rely on rigid actuators such as electric motors, but soft wall-climbing robots based on muscle-like actuators have not yet been achieved. Here, we report a tethered soft robot capable of climbing walls made of wood, paper, and glass at 90° with a speed of up to 0.75 body length per second and multimodal locomotion, including climbing, crawling, and turning. This soft wall-climbing robot is enabled by (i) dielectric-elastomer artificial muscles that generate fast periodic deformation of the soft robotic body, (ii) electroadhesive feet that give spatiotemporally controlled adhesion of different parts of the robot on the wall, and (iii) a control strategy that synchronizes the body deformation and feet electroadhesion for stable climbing. We further demonstrate that our soft robot could carry a camera to take videos in a vertical tunnel, change its body height to navigate through a confined space, and follow a labyrinth-like planar trajectory. Our soft robot mimicked the vertical climbing capability and the agile adaptive motions exhibited by soft organisms.

Adaptive Sliding Mode Control With Perturbation Estimation and PID Sliding Surface for Motion Tracking of a Piezo-Driven Micromanipulator

Abstract: This paper proposes an improved sliding mode control with perturbation estimation (SMCPE) featuring a PID-type sliding surface and adaptive gains for the motion tracking control of a micromanipulator system with piezoelectric actuation One advantage of the proposed controller lies in that its implementation only requires the online estimation of perturbation and control gains without acquiring the knowledge of bounds on system uncertainties The dynamic model of the system with Bouc-Wen hysteresis is established and identified through particle swarm optimization (PSO) approach, and the controller is designed based on Lyapunov stability analysis A high-gain observer is adopted to estimate the full state from the only measurable position information Experimental results demonstrate that the performance of proposed controller is superior to that of conventional SMCPE in both set-point regulation and motion tracking control Moreover, a submicron accuracy tracking and contouring is achieved by the micromanipulator with dominant hysteresis compensated for a low magnitude level, which validates the feasibility of the proposed controller in the field of micro/nano scale manipulation as well