arXiv subjects

Takuya Ikeda

Publications and source records attributed to Takuya Ikeda.

24 records · Page 2Linked to original sources

arXiv2020

Soft-Bubble grippers for robust and perceptive manipulation

Manipulation in cluttered environments like homes requires stable grasps, precise placement and robustness against external contact. We present the Soft-Bubble gripper system with a highly compliant gripping surface and dense-geometry visuotactile sensing, capable of multiple kinds of tactile perception. We first present various mechanical design advances and a fabrication technique to deposit custom patterns to the internal surface of the sensor that enable tracking of shear-induced displacement of the manipuland. The depth maps output by the internal imaging sensor are used in an in-hand proximity pose estimation framework -- the method better captures distances to corners or edges on the manipuland geometry. We also extend our previous work on tactile classification and integrate the system within a robust manipulation pipeline for cluttered home environments. The capabilities of the proposed system are demonstrated through robust execution multiple real-world manipulation tasks. A video of the system in action can be found here: [https://youtu.be/G_wBsbQyBfc].

cs.RO↗

arXiv2019

Direct Phase Locking of a Ti:Sapphire Optical Frequency Comb to a Remote Optical Frequency Standard

We report on an ultralow noise optical frequency transfer from a remotely located Sr optical lattice clock laser to a Ti:Sapphire optical frequency comb through telecom-wavelength optical fiber networks. The inherent narrow linewidth of the Ti:Sapphire optical frequency comb eliminates the need for a local reference high-finesse cavity. The relative fractional frequency instability of the optical frequency comb with respect to the remote optical reference was $6.7(1) \times 10^{-18}$ at 1 s and $1.05(3) \times 10^{-19}$ at 1,000 s including a 2.9 km-long fiber network. This ensured the optical frequency comb had the same precision as the optical standard. Our result paves the way for ultrahigh-precision spectroscopy and conversion of the highly precise optical frequency to radio frequencies in a simpler setup.

physics.ins-det↗

arXiv2015

Maximum Hands-off Control without Normality Assumption

Maximum hands-off control is a control that has the minimum L0 norm among all feasible controls. It is known that the maximum hands-off (or L0-optimal) control problem is equivalent to the L1-optimal control under the assumption of normality. In this article, we analyze the maximum hands-off control for linear time-invariant systems without the normality assumption. For this purpose, we introduce the Lp-optimal control with 0<p<1, which is a natural relaxation of the L0 problem. By using this, we investigate the existence and the bang-off-bang property (i.e. the control takes values of 1, 0 and -1) of the maximum hands-off control. We then describe a general relation between the maximum hands-off control and the L1-optimal control. We also prove the continuity and convexity property of the value function, which plays an important role to prove the stability when the (finite-horizon) control is extended to model predictive control.

eess.SY↗

arXiv2015

Discrete-Valued Control by Sum-of-Absolute-Values Optimization

In this paper, we propose a new design method of discrete-valued control for continuous-time linear time-invariant systems based on sum-of-absolute-values (SOAV) optimization. We first formulate the discrete-valued control design as a finite-horizon SOAV optimal control, which is an extended version of L1 optimal control. We then give simple conditions that guarantee the existence, discreteness, and uniqueness of the SOAV optimal control. Also, we give the continuity property of the value function, by which we prove the stability of infinite-horizon model predictive SOAV control systems. We provide a fast algorithm for the SOAV optimization based on the alternating direction method of multipliers (ADMM), which has an important advantage in real-time control computation. A simulation result shows the effectiveness of the proposed method.

eess.SY↗

arXiv2014

Value Function in Maximum Hands-off Control

In this brief paper, we study the value function in maximum hands-off control. Maximum hands-off control, also known as sparse control, is the L0-optimal control among the admissible controls. Although the L0 measure is discontinuous and non- convex, we prove that the value function, or the minimum L0 norm of the control, is a continuous and strictly convex function of the initial state in the reachable set, under an assumption on the controlled plant model. This property is important, in particular, for discussing the sensitivity of the optimality against uncertainties in the initial state, and also for investigating the stability by using the value function as a Lyapunov function in model predictive control.

eess.SY↗

arXiv2014

Continuity of the Value Function in Sparse Optimal Control

We prove the continuity of the value function of the sparse optimal control problem. The sparse optimal control is a control whose support is minimum among all admissible controls. Under the normality assumption, it is known that a sparse optimal control is given by L^1 optimal control. Furthermore, the value function of the sparse optimal control problem is identical with that of the L1-optimal control problem. From these properties, we prove the continuity of the value function of the sparse optimal control problem by verifying that of the L1-optimal control problem.

eess.SY↗