Sung-Kyun Kim

Bio: Sung-Kyun Kim is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Partially observable Markov decision process & Robot. The author has an hindex of 9, co-authored 38 publications receiving 303 citations. Previous affiliations of Sung-Kyun Kim include Jet Propulsion Laboratory & KAIST.

Autonomous Spot: Long-Range Autonomous Exploration of Extreme Environments with Legged Locomotion

Abstract: This paper serves as one of the first efforts to enable large-scale and long-duration autonomy using the Boston Dynamics Spot robot. Motivated by exploring extreme environments, particularly those involved in the DARPA Subterranean Challenge, this paper pushes the boundaries of the state-of-practice in enabling legged robotic systems to accomplish real-world complex missions in relevant scenarios. In particular, we discuss the behaviors and capabilities which emerge from the integration of the autonomy architecture NeBula (Networked Belief-aware Perceptual Autonomy) with next-generation mobility systems. We will discuss the hardware and software challenges, and solutions in mobility, perception, autonomy, and very briefly, wireless networking, as well as lessons learned and future directions. We demonstrate the performance of the proposed solutions on physical systems in real-world scenarios.

Design of a compact 5-DOF surgical robot of a spherical mechanism: CURES

Abstract: In recent years, several surgical or assistant robots have made a successful debut to surgical theatre. Due to their large size, and high price, there is a growing need for the miniaturization of these surgical robots. In this paper, a design methodology for a compact surgical robot is presented. Considering workspace and force requirements, a simulation and experiments are conducted to determine the design parameters. The compact surgical robot CURES of 5-DOF spherical mechanism is developed from the analysis and its properties are presented.

SLAP: Simultaneous Localization and Planning Under Uncertainty via Dynamic Replanning in Belief Space

Abstract: Simultaneous localization and planning (SLAP) is a crucial ability for an autonomous robot operating under uncertainty. In its most general form, SLAP induces a continuous partially observable Markov decision process (POMDP), which needs to be repeatedly solved online. This paper addresses this problem and proposes a dynamic replanning scheme in belief space. The underlying POMDP, which is continuous in state, action, and observation space, is approximated offline via sampling-based methods, but operates in a replanning loop online to admit local improvements to the coarse offline policy. This construct enables the proposed method to combat changing environments and large localization errors, even when the change alters the homotopy class of the optimal trajectory. It further outperforms the state-of-the-art Feedback-based Information RoadMap (FIRM) method by eliminating unnecessary stabilization steps. Applying belief space planning to physical systems brings with it a plethora of challenges. A key focus of this paper is to implement the proposed planner on a physical robot and show the SLAP solution performance under uncertainty, in changing environments and in the presence of large disturbances, such as a kidnapped robot situation.

A walking motion imitation framework of a humanoid robot by human walking recognition from IMU motion data

Abstract: Teleoperation of humanoid robots, which is one of good methods of humanoid utilization, has difficulties in locomotion with self-balancing. In this paper, we propose a framework of walking imitation between human and a humanoid robot. Using inertial measurement unit (IMU), human's walking motions are recognized, and used as humanoid robot control inputs for on-line walking imitation. Appropriate IMU feature data for walking recognition are investigated, and walking recognition method based on supporting foot detection and stance estimation is suggested. A humanoid robot is modeled as an inverted pendulum for on-line walking control. For validation, experiments were conducted using Mahru-R, a humanoid robot developed in KIST.

Autonomous Spot: Long-Range Autonomous Exploration of Extreme Environments with Legged Locomotion

Abstract: This paper serves as one of the rst efforts to enable large-scale and long-duration autonomy using the Boston Dynamics Spot robot. Motivated by exploring extreme environments, particularly those involved in the DARPA Subterranean Challenge, this paper pushes the boundaries of the state-of-practice in enabling legged robotic systems to accomplish real-world complex missions in relevant scenarios. In particular, we discuss the behaviors and capabilities which emerge from the integration of the autonomy architecture NeBula (Networked Belief-aware Perceptual Autonomy) with next-generation mobility systems. We will discuss the hardware and software challenges, and solutions in mobility, perception, autonomy, and very brie y, wireless networking, as well as lessons learned and future directions. We demonstrate the performance of the proposed solutions on physical systems in real-world scenarios.3 The proposed solution contributed to winning 1st-place in the 2020 DARPA Subterranean Challenge, Urban Circuit.4

Modelling and Control of Robot Manipulators

Abstract: Feel lonely? What about reading books? Book is one of the greatest friends to accompany while in your lonely time. When you have no friends and activities somewhere and sometimes, reading book can be a great choice. This is not only for spending the time, it will increase the knowledge. Of course the b=benefits to take will relate to what kind of book that you are reading. And now, we will concern you to try reading modelling and control of robot manipulators as one of the reading material to finish quickly.

Motion Capture from Inertial Sensing for UntetheredHumanoid Teleoperation

Abstract: We describe the design of a modular system for untethered real-time kinematic motion capture using sensors with inertial measuring units (IMU). Our system is comprised of a set of small and lightweight sensors. Each sensor provides its own global orientation (3 degrees of freedom) and is physically and computationally independent, requiring only external communication. Orientation information from sensors is communicated via wireless to host computer for processing. We present results of the real-time usage of our untethered motion capture system for teleoperating the NASA Robonaut. We also discuss potential applications for untethered motion capture with respect to humanoid robotics.

Bayesian Learning-Based Adaptive Control for Safety Critical Systems

Abstract: Deep learning has enjoyed much recent success, and applying state-of-the-art model learning methods to controls is an exciting prospect. However, there is a strong reluctance to use these methods on safety-critical systems, which have constraints on safety, stability, and real-time performance. We propose a framework which satisfies these constraints while allowing the use of deep neural networks for learning model uncertainties. Central to our method is the use of Bayesian model learning, which provides an avenue for maintaining appropriate degrees of caution in the face of the unknown. In the proposed approach, we develop an adaptive control framework leveraging the theory of stochastic CLFs (Control Lyapunov Functions) and stochastic CBFs (Control Barrier Functions) along with tractable Bayesian model learning via Gaussian Processes or Bayesian neural networks. Under reasonable assumptions, we guarantee stability and safety while adapting to unknown dynamics with probability 1. We demonstrate this architecture for high-speed terrestrial mobility targeting potential applications in safety-critical high-speed Mars rover missions.

The activities-specific balance confidence scale and the dizziness handicap inventory: a comparison.

Abstract: Vestibular dysfunction can have a tremendous impact on an individual's quality of life. The purpose of this paper is to determine if the level of handicap reported by individuals on the Dizziness Handicap Inventory (DHI), an inventory developed for use with individuals with complaints of dizziness symptoms, will be consistent with that reported on the Activities-specific Balance Confidence Scale (ABC), a tool developed for use with elderly individuals that attempts to assess a person's confidence level in performing activities of daily living (ADL's). A sample of convenience was used consisting of 71 subjects (15 males and 56 females) from a local Balance and Vestibular Clinic. The subjects ranged in age from 26 to 88 years of age. Both the DHI and the ABC were administered as part of an initial physical therapy evaluation to new patients at the clinic. A moderately strong negative correlation was found between the scores of the two inventories (Ts = -0.6350). The results suggest that the ABC is a valid tool for use with individuals with complaints of dizziness.

KITECH-Hand: A Highly Dexterous and Modularized Robotic Hand

Abstract: This paper presents an anthropomorphic robotic hand named “KITECH-Hand,” along with its kinematic analysis and detailed mechanical features. From a kinematic perspective, the authors particularly focus on the structure of the metacarpophalangeal (MCP) joints of the fingers. The KITECH-Hand adopts a new “roll–pitch”-type MCP structure to replace conventional “yaw–pitch” structures. The proposed structure provides benefits such as enhanced kinematic performance and ease of the mechanical design. Through the kinematic analysis, it is shown that the KITECH-Hand shows remarkably high dexterity, well surpassing that of existing robotic hands with conventional MCP joints. The unique MCP structure also helps modularize the robot at the joint level, which simplifies its mechanical structure and enables the production cost to be reduced. The performance of the KITECH-Hand, including its dexterity feature, was experimentally verified through a series of experiments, which included object in-hand manipulation and a Cutkosky taxonomy test.