A critical aspect in robot technology lies in ensuring that the robot arm executes the intended task or movement. The conventional teaching–playback technique for programming robot arm movements generates excessive torque when the initial posture differs from that during motion teaching or when external disturbances disrupt robotic arm execution. To address this problem, this study proposed a motion generation system with echo state networks (ESNs) for robot arms. These networks can reproduce trajectories including features such as attractors and bifurcations by training time-series data originating from a dynamical system. By leveraging this capability, the proposed approach enables an ESN to infer a dynamical system underlying demonstrated motions to perform a specific task on the basis of state feedback. Subsequently, the trained ESN generates reference signals to replicate the learned motion based on the current robot state. These reference signals can be used for linear feedback at the joint level. Redundant robots can easily transition to unobserved states because of their degrees of freedom. However, the trained ESN exhibits remarkable generalization capabilities, effectively guiding the robot back to its intended motion in those unobserved states. Numerical simulations confirmed that the proposed system dynamically adapts to robot behavior, effectively mitigating excessive acceleration, even in scenarios with initial posture deviations or external disturbances, thereby outperforming conventional teaching–playback methods.

Adaptive kinematic/dynamic control of a robot arm (manipulator) is important for the robust execution of various tasks, including target tracking, when changes in the environment and robot’s physical parameters, such as mass and friction, occur. For highly accurate model-free adaptive tracking control, we propose an error-correction model using the reservoir of basal dynamics (reBASICS) computing method. reBASICS is trained to minimize multimodal errors, such as those in the end-effector position (visually detected) and torques (proprioceptively detected), and to correct robot trajectories. If errors are corrected simultaneously, the corrections can interfere with each other. Therefore, the model initially corrects torques to stabilize robot movements, followed by position correction. In the simulation of a two-link robot arm, approximate inverse kinematics (IK) and proportional-derivative (PD) controllers were assumed to produce tracking errors. The results showed that reducing errors based on reBASICS produced smaller tracking errors from the reference trajectory compared to that using a conventional echo state network (ESN). Furthermore, reducing both position and torque errors resulted in better performance than reducing position-only and torque-only errors.

This paper extends the longitudinal walking controller of biped robots proposed by one of the authors to walking along a smooth curved path. The previous controller defined in a fixed inertial frame is redesigned with respect to a moving frame attached to the center of mass (COM) of the robot in order to achieve walking along an arc. As a result, it is found that a desired position of the zero-moment point (ZMP) can be determined only from the local curvature of the referential path besides the state of the robot with respect to the moving frame. Thus, it is directly applicable to walking along an arbitrary smooth path including straight walk. In addition to the extension of the ZMP manipulation, techniques of foot control consistent with COM movement and automatic update of the referential COM position are fully extended to curved walk. The idea was examined through computer simulations to show responsiveness to updates of motion references and robustness against external disturbances.

This paper addresses an omnidirectional locomotion control to make a biped robot walk back and forth, turn to any direction, move sideways and carry out them seamlessly. This is achieved by integrating smooth-path-tracking and lateral walking controllers that have been proposed by the authors, which is not straightforward because the path tracking is designed to converge to a referential path while the lateral walking aims to go away from the path. It can be avoided by extending the path-tracking controller to consecutively redraw the orbit that passes the middle of the feet. The proposed controller is designed completely in the robot-centric frame, namely, all the references and the manipulated variables are represented from the robot's viewpoint so that the operator can issue the referential values in the first-person view. Additionally, as the robot is ruled by neither a plan of footsteps nor time-dependent trajectories, it can flexibly respond to various perturbations. The validity of the proposed controller is investigated through computer simulations and an application to navigation of the robot is also shown.

This paper presents a repetitive hopping control of biped robots, which has the following properties: 1) It can initiate or cease hopping at any time, 2) The peak altitude can be freely altered during hopping, and 3) The impact at touchdown is suppressed. Hopping motions accompany frequent changes of contact conditions with the environment and lead the discontinuity of dynamics they are governed, therefore, it is difficult to achieve the motion in a way without relying any passive mechanisms such as springs and dampers. Three controllers, that is, (I) a regulator to stabilize, (II) a controller to converge a desired velocity when lifting off the ground and (III) a controller to absorb the landing impact are unified by the global scheme to transit each other depending on a commanded value and the state of the robot.

This paper presents a biped locomotion control to step sideways based on the framework of the dynamics morphing. Since the proposed controller does not require detailed referential motion trajectories, it enables a robot to walk sideways at arbitrary velocity given at random timing. Sideward locomotion is realized by alternating the velocity following control and the self-excited oscillating control accompanying with the exchange of the supporting foot. Techniques to automatically update the referential position of the center of mass and phase for the consistent footstep are also proposed.