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Due to copyright restrictions, the access to the full text of this article is only available via subscription. In this paper, we introduce a method that synergistically combines an analytical pattern generator and a feedback controller frame, which are developed for the purpose of synthesizing dynamic quadrupedal trot-walking locomotion on flat and uneven surfaces. To begin with, the pattern generator analytically produces feasible and dynamically balanced joint motions in accordance with the desired trot-walking characteristics, with no empirical parameter tuning requirements. In concurrence with the pattern generation, a two-phased controller frame is constructed for closed-loop sensory feedback: (i) virtual admittance controller via force sensing, (ii) upper torso angular momentum regulation via gyro sensing. The former controller evaluates joint force errors and generates the corresponding joint displacement for a given set of virtual spring-damper couples. Together with the position constraints, these displacements are additionally fed-back to local servos for achieving compliant quadrupedal locomotion with which the position/force trade-off is addressed. The second controller, that is simultaneously used, evaluates the upper torso angular momentum rate change error using measured and reference orientation information. It then regulates the torso orientation in a dynamically consistent way as the rotational inertia is characterized. In order to validate the proposed methodology several experiments are conducted on both flat and uneven surfaces, using two robots with distinct properties; a ∼7 kg cat-sized electrically actuated quadruped (RoboCat-1), and a ∼80 kg Alpine Ibex-sized hydraulically actuated quadruped (HyQ). As a result we demonstrate continuous, repetitive, compliant and dynamically balanced trot-walking cycles in real-robot experiments, adequately confirming the effectiveness of the proposed approach. Hitech Research Center ; Fondazione Istituto Italiano di Tecnologia

A mobile manipulator is a class of mobile robot on which the multi-link manipulator is mounted. This system is expected to play an important role both in the production process of factory and in the medical care system of welfare business. To come up to this expectation, a mobile manipulator is required to simultaneously track to both the desired position trajectory and force trajectory. However, these tracking performances are subject to nonholonomic and holonomic constraints. Furthermore, mobile manipulators possess complex and strongly coupled dynamics of mobile bases and manipulators. Then, there are very few studies on the problems of stabilization position/force control for mobile manipulators. In (Chang & Chen, 2002; Oya et al., 2003; Su et al., 1999), position and force control methods for mobile robot without manipulators have been addressed. Since in these studies holonomic constraints representing the interaction between end-effector of the manipulator and environment have not been considered, those approaches could not be applied to the position/force control problems of the mobile manipulators. In (Dong, 2002; Li et al., 2007; 2008), adaptive and robust control approaches have been applied to the position/force control problems of the mobile manipulators. In these approaches, since the chained form transforms are required, synthesismethods of the control torques and adaptation laws of these approaches are too complicated to apply. On the other hand, we have derived the stabilizing controllers for a class of mobile manipulators(Narikiyo et al., 2008). In (Narikiyo et al., 2008) we have proposed robust adaptive control scheme for the system with dynamic uncertainties and external disturbances directly from the reduced order dynamics subject to both the holonomic and nonholonomic constraints. Furthermore, in (Narikiyo et al., 2009) we have developed this control scheme to control the system with both kinematic and dynamic uncertainties. In these studies usefulness of these control schemes have been demonstrated by numerical examples. However, proof of the closed loop stability has not been completed under an inadequate assumption(Narikiyo et al., 2009). In this study we complete the proof and relax the assumptions of (Narikiyo et al., 2009). Then we implement these control schemes (Narikiyo et al., 2008; 2009) experimentally and apply to the prototype shown in Fig.1 to demonstrate the effectiveness of these proposed control schemes. It is also guaranteed theoretically that the tracking position and force errors to the desired trajectories are asymptotically converged to zero by the proposed control schemes. 7