Real-Time Accurate Simulation with Multi-Contact

Fast, accurate and stable simulation with multi-contact and tight-tolerance is crucial to data-driven approaches, e.g., deep reinforcement learning. Current robot simulators (e.g., ODE, Vortex, Bullet, etc.) do not provide this capability. For this, we propose a novel data-driven contact clustering based on the interaction network and trained with real experimental data. Combining this with our PMI (passive mid-point integrator, IJRR17), we could attain real-time, experimentally-validated simulation of peg-in-hole and bolting tasks with multi-contact and very tight tolerance, all impossible for other current simulators. (ICRA19)


Sim-to-Real Transfer of Tight-Tolerance Bolting Tasks

We propose a novel sim-to-real (S2R) framework for bolting tasks with tight tolerance and complex contact geometry. S2R is desirable for cost and safety,, yet, that of assembly task rare due to the lack of multi-contact simulator. We implement S2R transfer of nut tightening policy which is adaptive to uncertain bolt positions. For this, we develop a new multi-contact simulator, which adopt the configuration-space abstraction w/ fast/stable passive midpoint integrator (PMI). Sampling-based motion planning and LQT are used for nominal controller to be compliant and avoid local optima, whereas RL is used as a high-level controller to adapt to the uncertainty. (IROS2020)

Large-Scale Dual-Arm System on Flexible Support 

We design a control law for the height-task teleoperation system, consisting of two KUKA LWRs, an actuated stage and a 10-meter telescoping mast (system developed by KAERI). Control objective is to allow end-effector to precisely track (unpredictable) human command, while suppressing mast vibration. To ensure robustness while handling with large system DOF (27), passive decomposition and passivity-based control techniques are adopted. Further, onboard sensing is attained attaching IMUs to each mast segment and utilizing data-driven POD/MAP estimation technique (ICRA19).

Under-Actuated Tendon-Driven Robot

​We present a novel design framework for general under-actuated tendon-driven (UATD) robots to mimic desired free motion while maintaining posture during contact operations. The key enabler is stiffness decomposition, which allows us to decompose UATD robot into actuated and un-actuated space, thereby, allowing us to attain compliant free motion, while minimizing un-actuated space deformation. Design optimization is also proposed, which automatically provides active/passive tendon routing, joint spring, pre-tension, etc.  (ICRA2018)

Arm-Stage System on Vertical Beam

Simultaneous trajectory tracking and vibration stabilization control of manipulator-stage system on vertical flexible beam, which will be used for operation in height. Euler-Bernoulli and Lagrange dynamics formulation are used with certain boundary conditions to model the system. Coordinate transformation and passive decomposition are used to decompose the total 7-DOF dynamics (4-DOF for arm+stage and 3-DOF for vibration) into vibration+stage and tracking objective. Passivity-based control with damping injection control is then design to these decomposed dynamics. EF-tracking experiment is performed to show the efficacy, for which the typical null-space based tracking control becomes unstable. (IROS2017)

PBC of Nonholonomic Systems

Passivity-based control (PBC) has been widely used for robotic manipulators with its superior robustness as compared to feedback linearization due to its exploitation of open-loop nonlinear dynamics rather than cancel them out.  This passivity-based approach, yet, has been surprisingly missing for nonholonomic mechanical systems.  In this work, we present passivity-based stabilization control for a certain class of nonholonomic systems.  For this, we establish passive configuration decomposition (PCD) and propose passivity-based time-varying and switching controls. We also manifest when PCD is possible; and also establish equivalence of the proposed controls with kinematic controllability. (T-RO2017)

Passive Decomposition Theory

Passivity is a fundamental property of mechanical systems with close connection with Lyapunov control synthesis.  At the same time, task can often be described by holonomic map h(q) (e.g., grasping shape).  For this, we develop the theory of passive decomposition, i.e., we can decompose open-loop Lagrange robot dynamics into: (1) shape system, describing h(q)-dynamics; (2) locked system, describing system behavior with h(q) fixed; and (3) passive coupling between them. Locked and shape systems individually inherit Lagrange structure and passivity, greatly facilitating control design. Passive decomposition has been extended to Riemannian manifold and nonholonomic systems. (T-RO2010, T-AC2013)

Control of Under-Actuated UAVs

Quadrotor UAV is an under-actuated system, that is, its-DOF is 6 evolving in SE(3), yet, its actuation is only 4-DOF (i.e., 4 rotors).  We investigated the issue of control of this under-actuated quadrotor UAVs. In particular, we utilize backstepping control technique to overcome its under-actuation and also combine it with adaptation to address inertial uncertainty. We also extend this backstepping framework to distributed control of multiple quadrotors with their information flow constrained by a balanced graph. (Automatica2012RAS2014, Best Paper Award IAS2012)