This article proposes a betterment process for the operation of a mechanical robot in a sense that it betters the next operation of a robot by using the previous operation's data. The process has an iterative learning structure such that the (k + 1)th input to joint actuators consists of the kth input plus an error increment composed of the derivative difference between the kth motion trajectory and the given desired motion trajectory. The convergence of the process to the desired motion trajectory is assured under some reasonable conditions. Numerical results by computer simulation are presented to show the effectiveness of the proposed learning scheme.

This paper proposes a stable tracking control rule for non-bolonomic vehicles. Stability of the rule is proved through the use of a Liapunov function. Input to the vehicle are a reference posture (x,, y,, 8,)' and reference velocities (v,, ar)'. The major objective of this paper is to propose a control rule to find a reasonable target linear and rotational velocities (v, a ) ' .Linearizing the system's differential equation is useful to decide parameters for critical dumping for a small disturbance. In order to avoid any slippage, a velocity/acceleration limitation scheme was introduced. Several siniulation results are presented with or without the velocity/acceleration limiter. The control rule and limiting method proposed in this paper are robot-independent and hence can be applied to various kind of mobile robots with a dead reckoning ability. This method was implemented on the autonomous mobile robot Yamabico-11.Experimental results obtained are close to the results with the velocity/acceleration limiter.

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The major objective of this paper is to propose a stable control rule to find a reasonable target linear and rotational velocities (v, w)'. The stability of the rule is proved through the use of a Liapunov function. The rule contains three parameters, Kx, Ky and Ke. Although any set of positive parameters makes the system stable, a condition on the parameters for the system being critically damped for a small disturbance is obtained through linearizing the system's differential equation. This method was successfully implemented on the autonomous mobile robot Yamabico-11. Experimental results obtained tum out to be close to the results with the velocity/acceleration limiter.

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