In the context of touch-based object localisation, solving the problem of “where to sense next” is a challenging task due to the curse of dimensionality related to belief-state reasoning. We present a constrained optimisation scheme that computes the next best action maximising the trade off between (i) the localisation information gain, (ii) the time required for its computation, and (iii) the motion-execution time. This allows the robot programmer to have a deterministic influence on the length of every sensing action. The proposed methodology is applied to localise a solid object in 3D using a Staubli RX90 robot equipped with a force-torque sensor coupled with a spherical end effector. A case-study comparison of the task executed with two different time constraints is presented.

A vision-based vibration suppression scheme has previously been proposed to control the vibrational behaviour of long-reach arms operating in fusion reactors. In this paper we describe a new method to reconstruct the vibration using sinusoidal regression. This change makes the overall scheme more efficient since it enables the estimation of the tip oscillation whatever its origin may be. Both an exact solution and a simplified method are proposed to solve the regression problem. To limit the trade-off between good tracking capability and quality of the vibration reconstruction, these regression algorithms are performed over a variable-length sliding window. Consequently this paper also describes the change detection scheme used to automatically adjust the window length. Experimental results validate the proposed method.

In this paper we present a vibration control scheme for a long-reach inspection arm in an environment as constrained as a fusion reactor. The ultra-high vacuum, the high operating temperature, the significant residual magnetic field and the nuclear activation in ITER will prevent from considering common on-the-shelf dynamics sensors. Therefore we propose to use the already developed rad-hardened viewing tool to feed an oscillation observer with visual information. In our approach the visual data are extracted from a totally unknown environment. Particular attention is paid to obtain a robust algorithm. Experimental results validate the proposed strategy.

This paper presents the developments carried out at CEA LIST to adapt the 6-DOF hydraulic manipulator Maestro to work with pure water instead of oil. Its elbow joint has been redesigned for water applications and a prototype of water hydraulic pressure servovalve has been manufactured. Both performances of the actuator and its pre-actuator are discussed. A model of the servovalve is proposed to identify its driving parameters and validate the next evolutions in its design, anticipating the second generation of prototypes.