Tomomichi Sugihara

Real-time humanoid motion generation through ZMP manipulation based on inverted pendulum control

A humanoid robot is expected to be a rational form of machine to act in the real human environment and support people through interaction with them. Current humanoid robots, however, lack in adaptability, agility, or high-mobility enough to meet the expectations. In order to enhance high-mobility, the humanoid motion should be generated in real-time in accordance with the dynamics, which commonly requires a large amount of computation and has not been implemented so far. We have developed a real-time motion generation method that controls the center of gravity (COG) by indirect manipulation of the zero moment point (ZMP). The real-time response of the method provides humanoid robots with high-mobility. In the paper, the algorithm is presented. It consists of four parts, namely, the referential ZMP planning, the ZMP manipulation, the COG velocity decomposition to joint angles, and local control of joint angles. An advantage of the algorithm lies in its applicability to humanoids with a lot of degrees of freedom. The effectiveness of the proposed method is verified by computer simulations.

Whole-body cooperative balancing of humanoid robot using COG Jacobian

Since humanoid robots have a number of degrees-of-freedom in general, a pattern-based approach of the motion control reduces its difficulty. It is necessary, however, to absorb and compensate disturbances in order to maintain the stability of robots in the real world. We developed a balancing method for humanoid robots with a little modification of predesigned motion trajectories. The method proposed has an advantage that it is allowed to choose any combination of joints as modified properties, so that it has enough flexibility, being applicable for various types of robots and motions. It consists of two phases; in the first phase, the referential COG displacement is decided in accordance with both the short-term and the long-term absorption of disturbances. And in the second phase, the COG is manipulated with the whole-body cooperation, using the COG Jacobian. We verified the validity of the method with some simulations.

A Fast Dynamically Equilibrated Walking Trajectory Generation Method of Humanoid Robot

This paper describes a fast dynamically equilibrated trajectory generation method for a humanoid robot. From a given input motion and the desired ZMP trajectory, the algorithm generates a dynamically equilibrated trajectory using the relationship between the robots center of gravity and the ZMP. Three key issues are denoted: 1) an enhanced ZMP constraint which enables the calculation of robot stability even if several limbs are contacting the environment, 2) a simplified robot model is introduced that represents the relationship between its center of gravity and ZMP, 3) a convergence method is adopted to eliminate approximation errors arising from the simplified model. Combining these three key issues together with online ZMP compensation method, humanoid robot H5 have succeeded to walk, step down and so on. Experimental results using humanoid robot H5 are described.

A Fast Online Gait Planning with Boundary Condition Relaxation for Humanoid Robots

A fast online gait planning method is proposed. Based on an approximate dynamical biped model whose mass is concentrated to COG, general solution of the equation of motion is analytically obtained. Dynamical constraint on the external reaction force due to the underactuation is resolved by boundary condition relaxation, namely, by admitting some error between the desired and actually reached state. It potentially creates responsive motion which requires strong instantaneous acceleration by accepting discontinuity of ZMP trajectory, which is designed as an exponential function. A semi-automatic continuous gait planning is also presented. It generates physically feasible referential trajectory of the whole-body only from the next desired foot placement. The validity of proposed is ensured through both simulations and experiments with a small anthropomorphic robot.

Standing stabilizability and stepping maneuver in planar bipedalism based on the best COM-ZMP regulator

The goal of this paper is to answer (i) how the stabilization performance of a biped controller can be evaluated on a certain invariant supporting region, (ii) how the standing stabilizer which performs the best on a given supporting region can be designed, (iii) how the system can be judged if it is stabilizable by the best standing stabilizer without deforming the current supporting region, and (iv) how the supporting region should be deformed if it is judged to be necessary. In order to answer these question, the stable standing region is defined. It gives a criterion to design the best standing stabilizer, to judge if the deformation of the supporting region is necessary to stabilize the system, and to maneuver the stepping motion in accordance with the standing stabilizability condition, which is also defined in the paper. It is found that the best standing stabilizer can be designed by a simple pole-assignment technique. This framework unifies the standing stability and the stepping stability of bipedalism, which have been separately considered in conventional studies. The discussion goes on an approximate planar COM-ZMP model, in which the total mass is concentrated at the center of mass, and the position of ZMP is regarded as the input. Though it is the simplest dynamical model of bipeds, it can conceal differences of body constitutions and represent the macroscopic dynamics. Therefore, this paper contributes to not only the biped robot controller design but also the biomechanical analyses.

Design and implementation of software research platform for humanoid robotics: H6

The H6 humanoid robot has been developed as a platform for the research on perception-action coupling in intelligent behaviour of humanoid type robots. The H6 features: 1) a body which has enough DOFs and each joint has enough torque for full body motion; 2) a PC/AT compatible high-performance on-board computer which is controlled by RT-Linux so that from low-level to high-level control is achieved simultaneously; 3) self-contained and connected to a network via radio Ethernet; and 4) dynamic walking trajectory generation, motion planning and 3D vision functions are available. The H6 can be used as a common test-bed in experiment for various aspects of intelligent humanoid robotics.

Solvability-Unconcerned Inverse Kinematics by the Levenberg–Marquardt Method

A robust numerical solution to the inverse kinematics is proposed based on the Levenberg-Marquardt (LM) method, where the squared norm of residual of the original equation with a small bias is used for the damping factor. A rather simple idea remarkably improves the numerical stability and the convergence performance, even in unsolvable cases. Discussion is done through an investigation of the condition number of the coefficient matrix. Comparison tests with conventional methods show that only the proposed method succeeds in all cases. It frees operators from being careful about the target position-orientation assignment of effectors so that it facilitates easy robot motion designs and remote operations.

Boundary Condition Relaxation Method for Stepwise Pedipulation Planning of Biped Robots

A completely stepwise online pedipulation planning method is proposed. It is an analytical approach based on the general solution of the equation of motion of an approximate dynamical biped model whose mass is concentrated at the center of mass. A physically feasible referential trajectory with a constraint about the reaction force taken into account is planned only in one interval by relaxing the boundary condition, namely, by admitting a certain level of error between the desired and actually reached states, and discontinuity of zero-moment point at each end of the interval. It potentially creates responsive motions that require strong instantaneous acceleration. A semiautomatic continual pedipulation planning method is also presented. It generates a referential trajectory of the whole body only from the next desired foot placement. The validity of the proposed method is ensured through experiments with a small anthropomorphic robot.

Primitive communication based on motion recognition and generation with hierarchical mimesis model

Communication skill is essential for social robots in various environments such as homes, offices, and hospitals, where the robots are expected to interact with humans. In this paper, we model the primitive nonverbal communication between two persons by mimetic communication model. The model consists of three groups of hidden Markov models (HMMs) hierarchically combined to recognize motions of the human and to generate the interactive motions of the robot. HMMs in the lower layer abstract the motion patterns and HMMs in the upper layer represent the interaction patterns. We demonstrate the validity of this model through kick boxing match between a motion-captured human and humanoid robot, where the robot can autonomously generate its motion in response to attacks by the human

Hardware design of high performance miniature anthropomorphic robots

Technical issues in designing reliable high-performance miniature humanoid robots are discussed. Although the light-weight and small-size body of such a humanoid robot facilitates safer and smoother experiments of agile motions involving large accelerations and impacts, building a complex humanoid system in a small body is still a challenging problem. Simultaneous requirements for wider motion ranges, higher rigidity, less fragile electric devices and circuits, and less sensitive electric wiring should be satisfied in a limited space. In order to meet them by overcoming the difficulties, we propose to mechanically modularize joint structures, and to equip a centralized electric control unit involving PC boards, sensing devices, signal-processors, communication boards, and power amplifiers. The developments of the mechanical modules and the centralized unit are made for two miniature humanoid robots.