Jaeheung Park
Seoul National University · 工学
研究室紹介
Professor Jaeheung Park's research lab specializes in advanced robotics control, with a focus on operational space control, compliant motion control, and humanoid robot dynamics. The lab develops innovative frameworks for force and motion control in complex robotic systems, particularly in scenarios involving multiple contacts, singularities, and environmental interactions. Key research directions include transparent teleoperation, robust force control using state estimation, and real-time localization for autonomous systems such as self-parking vehicles. The lab integrates theoretical control design with experimental validation, emphasizing practical applications in humanoid robotics and intelligent automation.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15This paper presents a new teleoperation approach using a virtual spring, and local contact force control on the slave robot. The operational space framework provides the control structure needed to achieve decoupled task dynamics. A virtual spring connects the master and slave systems and a closed-loop force controller compensates for the dynamics of the slave system, rendering transparent the effector of the slave robotic system. The active force control approach allows the desired motion and c
This paper presents a framework for the dynamical formulation and control of humanoid systems. In this framework unactuated virtual joints are used to describe the humanoid's configuration with respect to the inertial frame. The dynamics of the system are then formulated in a general manner that considers arbitrary contact with the environment. A control structure is implemented for both motion and contact forces that accounts for under-actuation due to the virtual joints. A strategy is also imp
SUMMARY This paper addresses the problem of contact force control for multiple contacts distributed over multiple links in a robot. This is of importance when performing complex tasks in unstructured environment, particularly in humanoid robot applications. The proposed multicontact control framework provides a new way of defining the operational space coordinates, which facilitates the specification of multiple contact control. The contact force space on multiple links is constructed as an oper
When robots are controlled in the task space, singularities and joint limits are among the most critical and difficult issues that can arise. In this paper, we propose a new approach for the robots to operate in the regions near singularities and joint limits using the operational space control framework. Specifically, a continuous task transition algorithm called the intermediate desired value approach is applied to the hierarchically structured controller in the operational space control frame
This paper presents a compliant motion control framework for multiple contacts distributed over multiple links. The one link multi-contact control approach implemented in our previous work has been extended to contacts over multiple links. Experimental results demonstrate three point contact control on two links of a PUMA560 manipulator. A robust force control design is implemented with a Kalman estimator and full state feedback method to compensate for the modeling errors of the manipulator and
Parking is a challenging task for autonomous vehicles and requires a centimeter level precision of distance measurement for safe parking at a destination to avoid collisions with nearby vehicles. In order to avoid collisions with parked vehicles while parking, real-time localization performance should be maintained even when loop closing occurs. This study proposes a simultaneous localization and mapping (SLAM) method, using around view monitor (AVM)/light detection and ranging (LiDAR) sensor fu
This paper presents the technical approaches used and experimental results obtained by Team SNU (Seoul National University) at the 2015 DARPA Robotics Challenge (DRC) Finals. Team SNU is one of the newly qualified teams, unlike 12 teams who previously participated in the December 2013 DRC Trials. The hardware platform THORMANG, which we used, has been developed by ROBOTIS. THORMANG is one of the smallest robots at the DRC Finals. Based on this platform, we focused on developing software architec
Semi-structured environments are difficult for autonomous driving because there are numerous unknown obstacles in drivable area without lanes, and its width and curvature considerably change. In such environments, searching for a path on a real-time is difficult, and localization data are inaccurate, reducing path tracking accuracy. Instead, alternative methods that reactively avoid obstacles in real-time using candidate paths or an artificial potential field have been studied. However, these re