Multiple cooperating manipulators: The case of kinematically redundant arms

Existing work concerning two or more manipulators simultaneously grasping and transferring a common load is continued and extended. Specifically considered is the case of one or more arms being kinematically redundant. Some existing results in the modeling and control of single redundant arms and multiple manipulators are reviewed. The cooperating situation is modeled in terms of a set of coordinates representing object motion and internal object squeezing. Nominal trajectories in these coordinates are produced via actuator load distribution algorithms introduced previously. A controller is developed to track these desired object trajectories while making use of the kinematic redundancy to additionally aid the cooperation and coordination of the system. It is shown how the existence of kinematic redundancy within the system may be used to enhance the degree of cooperation achievable

Stochastic differential games with multiple modes

We have studied two person stochastic differential games with multiple modes. For the zero-sum game we have established the existence of optimal strategies for both players. For the non zerosum case we have proved the existence of a Nash equilibrium

Estimation and analysis of nonlinear stochastic systems.

Thesis. 1975. Ph.D.--Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.Vita.Bibliography: leaves 147-157.Ph.D

A framework for mixed estimation of hidden Markov models

In this paper, we present a framework for a mixed estimation scheme for hidden Markov models (HMM). A robust estimation scheme is first presented using the minimax method that minimizes a worst case cost for HMMs with bounded uncertainties. Then we present a mixed estimation scheme that minimizes a risk-neutral cost with a constraint on the worst-case cost. Some simulation results are also presented to compare these different estimation schemes in cases of uncertainties in the noise model

Risk-Sensitive Optimal Control of Hidden Markov Models: A Case Study

We consider a risk-sensitive optimal control problem for hidden Markov models (HMM). Building upon recent results by Baras, James and Elliott, we investigate the structure of risk-sensitive controllers for HMM, via an examination of a popular benchmark problem. We obtain new results on the structure of the risk- sensitive controller by first proving concavity and piecewise linearity of the value function. Furthermore, we compare the structure of risk-sensitive and risk-neutral controllers

Stochastic Differential Games with Multiple Modes

We have studied two-person stochastic differential games with multiple modes. For the zero-sum game we have established the existence of optimal strategies for both players. For the non- zero sum case we have proved the existence of a Nash equilibrium

Risk-Sensitive Optimal Control of Hidden Markov Models: Structural Results

We consider a risk-sensitive optimal control problem for hidden Markov models (HMM), i.e. controlled Markov chains where state information is only available to the controller via an output (message) process. Building upon recent results by Baras, James and Elliott, we report in this paper result of an investigation on the nature and structure of risk-sensitive controllers. The question we pose is: How does risk-sensitivity manifest itself in the structure of a controller? We present the dynamic programming equations for risk-sensitive control of HMMs and show a number of structural properties of the value function (e.g., concavity and piecewise linearity) and the optimal risk-sensitive controller, and compare these to the corresponding results for the risk- neutral case. Furthermore, we show that indeed the risk-sensitive controller and its corresponding information state converge to the known solutions for the risk-neutral situation, as the risk factor goes to zero. We also study the infinite and general risk aversion cases. In addition, we present a particular case study of a popular benchmark machine replacement problem