The Experts below are selected from a list of 273 Experts worldwide ranked by ideXlab platform
Ikuo Mizuuchi - One of the best experts on this subject based on the ideXlab platform.
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end tip speed maximization for noncyclic swing motion based on time reversal integral in multiple joint robots
International Conference on Robotics and Automation, 2015Co-Authors: Takatoshi Hondo, Ikuo MizuuchiAbstract:This paper describes a control method for noncyclic swing motions such as throwing, hitting and kicking in multiple-joint robots by using “time reversal integral.” This method calculates a control input sequence and an initial posture of the robot to reach a designated Terminal State by integrating a dynamic system without directly designating trajectories. The Terminal end-tip speed is maximized by optimizing the target Terminal State under constraints such as friction and the joint position limits. Feasibility of the method is evaluated by ball throwing experiments.
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ICRA - End-tip speed maximization for noncyclic swing motion based on time reversal integral in multiple-joint robots
2015 IEEE International Conference on Robotics and Automation (ICRA), 2015Co-Authors: Takatoshi Hondo, Ikuo MizuuchiAbstract:This paper describes a control method for noncyclic swing motions such as throwing, hitting and kicking in multiple-joint robots by using “time reversal integral.” This method calculates a control input sequence and an initial posture of the robot to reach a designated Terminal State by integrating a dynamic system without directly designating trajectories. The Terminal end-tip speed is maximized by optimizing the target Terminal State under constraints such as friction and the joint position limits. Feasibility of the method is evaluated by ball throwing experiments.
Takatoshi Hondo - One of the best experts on this subject based on the ideXlab platform.
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end tip speed maximization for noncyclic swing motion based on time reversal integral in multiple joint robots
International Conference on Robotics and Automation, 2015Co-Authors: Takatoshi Hondo, Ikuo MizuuchiAbstract:This paper describes a control method for noncyclic swing motions such as throwing, hitting and kicking in multiple-joint robots by using “time reversal integral.” This method calculates a control input sequence and an initial posture of the robot to reach a designated Terminal State by integrating a dynamic system without directly designating trajectories. The Terminal end-tip speed is maximized by optimizing the target Terminal State under constraints such as friction and the joint position limits. Feasibility of the method is evaluated by ball throwing experiments.
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ICRA - End-tip speed maximization for noncyclic swing motion based on time reversal integral in multiple-joint robots
2015 IEEE International Conference on Robotics and Automation (ICRA), 2015Co-Authors: Takatoshi Hondo, Ikuo MizuuchiAbstract:This paper describes a control method for noncyclic swing motions such as throwing, hitting and kicking in multiple-joint robots by using “time reversal integral.” This method calculates a control input sequence and an initial posture of the robot to reach a designated Terminal State by integrating a dynamic system without directly designating trajectories. The Terminal end-tip speed is maximized by optimizing the target Terminal State under constraints such as friction and the joint position limits. Feasibility of the method is evaluated by ball throwing experiments.
Raymond Rishel - One of the best experts on this subject based on the ideXlab platform.
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Estimating the Terminal State of a maneuvering target
Proceedings of 1994 33rd IEEE Conference on Decision and Control, 1994Co-Authors: V.e. Benes, Kurt Helmes, Raymond RishelAbstract:Consider a maneuvering target whose State x/sub t/ is governed by the linear stochastic system dx/sub t/=(Ax/sub t/+Bu/sub t/)dt+/spl sigma/dW/sub t/ in which u/sub t/ is the target's control law and W/sub t/ is a Wiener process of disturbances. Let linear observations y/sub t/ satisfying dy/sub t/=Hx/sub t/dt+dV/sub t/ be made, where V/sub t/ is a Wiener process of measurement errors. V/sub t/ and W/sub t/ are assumed to be statistically independent random processes. It is desired to estimate where the target will be, at a fixed final time T, from the measurements y/sub s/ made on the interval 0/spl les/s/spl les/t. However, the target's maneuverings, that is the function it selects for its control law, are unobservable. Since this is the case, treat the target's control law as a random process, and assume that it is possible to give a prior probability distribution for this random process. Let us also assume that there is a prior probability distribution for the target's initial State so which is Gaussian with mean C1 and covariance matrix C. The objective of this paper is to give computationally implementable formulas for computing the conditional expectation of the target's Terminal State given the past measurements. >
V.e. Benes - One of the best experts on this subject based on the ideXlab platform.
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Estimating the Terminal State of a maneuvering target
Proceedings of 1994 33rd IEEE Conference on Decision and Control, 1994Co-Authors: V.e. Benes, Kurt Helmes, Raymond RishelAbstract:Consider a maneuvering target whose State x/sub t/ is governed by the linear stochastic system dx/sub t/=(Ax/sub t/+Bu/sub t/)dt+/spl sigma/dW/sub t/ in which u/sub t/ is the target's control law and W/sub t/ is a Wiener process of disturbances. Let linear observations y/sub t/ satisfying dy/sub t/=Hx/sub t/dt+dV/sub t/ be made, where V/sub t/ is a Wiener process of measurement errors. V/sub t/ and W/sub t/ are assumed to be statistically independent random processes. It is desired to estimate where the target will be, at a fixed final time T, from the measurements y/sub s/ made on the interval 0/spl les/s/spl les/t. However, the target's maneuverings, that is the function it selects for its control law, are unobservable. Since this is the case, treat the target's control law as a random process, and assume that it is possible to give a prior probability distribution for this random process. Let us also assume that there is a prior probability distribution for the target's initial State so which is Gaussian with mean C1 and covariance matrix C. The objective of this paper is to give computationally implementable formulas for computing the conditional expectation of the target's Terminal State given the past measurements. >
Ulrich Horst - One of the best experts on this subject based on the ideXlab platform.
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Mean-Field Leader-Follower Games with Terminal State Constraint
SIAM Journal on Control and Optimization, 2020Co-Authors: Ulrich HorstAbstract:We analyze linear McKean--Vlasov forward-backward SDEs arising in leader-follower games with mean-field type control and Terminal State constraints on the State process. We establish an existence a...
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Continuous Viscosity Solutions to Linear-Quadratic Stochastic Control Problems with Singular Terminal State Constraint
Applied Mathematics & Optimization, 2020Co-Authors: Ulrich Horst, Xiaonyu XiaAbstract:This paper establishes the existence of a unique nonnegative continuous viscosity solution to the HJB equation associated with a linear-quadratic stochastic control problem with singular Terminal State constraint and possibly unbounded cost coefficients. The existence result is based on a novel comparison principle for semi-continuous viscosity sub- and supersolutions for PDEs with singular Terminal value. Continuity of the viscosity solution is enough to carry out the verification argument.
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Mean-Field Leader-Follower Games with Terminal State Constraint
2018Co-Authors: Ulrich HorstAbstract:We analyze linear McKean-Vlasov forward-backward SDEs arising in leader-follower games with mean-field type control and Terminal State constraints on the State process. We establish an existence and uniqueness of solutions result for such systems in time-weighted spaces as well as a {convergence} result of the solutions with respect to certain perturbations of the drivers of both the forward and the backward component. The general results are used to solve a novel single-player model of portfolio liquidation under market impact with expectations feedback as well as a novel Stackelberg game of optimal portfolio liquidation with asymmetrically informed players.
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Continuous viscosity solutions to linear-quadratic stochastic control problems with singular Terminal State constraint
2018Co-Authors: Ulrich Horst, Xiaonyu XiaAbstract:This paper establishes the existence of a unique nonnegative continuous viscosity solution to the HJB equation associated with a Markovian linear-quadratic control problems with singular Terminal State constraint and possibly unbounded cost coefficients. The existence result is based on a novel comparison principle for semi-continuous viscosity sub- and supersolutions for PDEs with singular Terminal value. Under a mild additional assumption on the model parameters we show that the viscosity solution is in fact a $\pi$-strong solution to the HJB equation and can hence be compactly approximated by smooth functions.
