This study proposes a biped-robot pelvis-kinematics estimator based on the touch-point updating method. Because the pelvis frame is used as the base coordinate for the control, the kinematics of it with respect to the global frame should be precisely estimated. To this end, it was necessary to know where the robot made contact with the ground. The touch-point concept was introduced as the temporal contact-point, which was instantly the robot's rotation center. By updating this point, the biped's global pelvis-kinematics could be estimated. The proposed estimator was implemented into the actual robot, and its superiority was verified through ground-truth data.

This work proposes a humanoid robot center of mass (COM) estimation framework based on the compliant inverted pendulum model and the robust estimator. Humanoids' limited structural stiffness and relatively long legs result in undesired flexibility, and this undesired motion hinders the state estimation. The models used in previous studies were either not suitable for estimation or too simple to express these key characteristics of humanoid robots. Here, to enhance the estimation performance, the compliant inverted pendulum model, which is developed by attaching a spring and damper to the original pendulum, is adopted. The additional elements can represent the mechanical deformation and undesired flexibility. This model can reflect the important characteristics of the humanoid robot while taking advantage of the merits of the sing-mass model. In addition, a robust state estimator that was proposed in our previous work is adopted to compensate for an estimation error caused by a modeling error. Using these two factors, an improved COM kinematics estimates could be obtained.

Most state-of-the-art torque control-based legged robots show excellent performance, exceeding that of conventional position control-based robots. Many conventional position control-based legged robots have high gear ratios, but do not have joint torque sensors. In addition, some robots cannot generate current for controlling the motor torque. To apply torque control-based walking algorithms to a position control-based humanoid robot, we proposed current control using a motor thermal model and realized joint torque control by compensating for the joint dynamics and robot dynamics. We conducted experiments to verify the performance of the Hubo2 platform developed in 2008 by applying a full-body dynamics control framework. The results confirmed the possibility of using torque control algorithms with existing position-based robots.

This paper describes a humanoid robotics platform (DRC-HUBO+) developed for the Defense Advanced Research Projects Agency Robotics Challenge (DRC) Finals. This paper also describes the design criteria, hardware, software framework, and experimental testing of the DRC-HUBO+ platform. The purpose of DRC-HUBO+ is to perform tasks by teleoperation in hazardous environments that are unsafe for humans, such as disaster zones. We identified specific design concepts for DRC-HUBO+ to achieve this goal. For a robot to be capable of performing human tasks, a human-like shape and size, autonomy, mobility, manipulability, and power are required, among other features. Furthermore, modularized joints and a user-friendly software framework were emphasized as design concepts to facilitate research on the robot tasks. The DRC-HUBO+ platform is based on DRC-HUBO-1 and HUBO-2. The torque of each joint is increased compared to that in DRC-HUBO-1 owing to its high reduction ratio and air-cooling system. DRC-HUBO+ is designed with an exoskeletal structure to provide it with sufficient stiffness relative to its mass. All wires are enclosed within the robot body using a hollow shaft and covers to protect the wires from external shock. Regarding the vision system, active cognition of the environment can be realized using a light-detection and ranging sensor and vision cameras on the head. To achieve stable mobility, the robot can transition from the bipedal walking mode to the wheel mode using wheels located on both knees. DRC-HUBO+ has 32 degrees of freedom (DOFs), including seven DOFs for each arm and six DOFs for each leg, and a solid and light body with a height of 170 cm and a mass of 80 kg. A software framework referred to as PODO, with a Linux kernel and the Xenomai patch, is used in DRC-HUBO+.

The unified approach algorithm to control a mobile robot is useful in simplifying path planning and inverse kinematics by considering a mobile platform as hypothetical joints. Applying the damped least square method by using the Jacobian prevents the divergence of the joint angle. However, it is possible to violate the nonholonomic constraint on mobility by distorting the Jacobian. In robot manipulation, the end-effector position error due to a violation of the constraint can be fatal, because such an error can damage a nearby object or the robot itself. In this paper, we propose a method that strictly guarantees nonholonomic constraints on a mobile manipulator. We also propose a compensation technique for faster convergence of the position and orientation of the end effector. The effectiveness of the proposed methods was confirmed through simulations.

In this paper we introduce a biped foot placement controller based on capture point (CP) feedback control. This capture point feedback controller generates desired Zero Moment Point (ZMP) according to current capture point error. We call this desired ZMP as Control-ZMP (cZMP). Using this cZMP, we constructed (i) a disturbance adapting walking pattern generator, (ii) an ankle torque reference generator, (iii) a landing foot position adjustor and, (iv) a step time adjustor. By applying these controllers, the biped system becomes robust over uneven terrain and external pushing disturbances. We considered cZMP as a key indicator of bipedal walking stability. If the cZMP is within the support polygon, the robot will track the cZMP by using (i) and (ii). If the cZMP is outside of the support polygon, the robot will change footstep position and time by using (iii) and (iv) (COM pattern will be changed by (i) too). Capture point dynamics is described based on a linear inverted pendulum (LIP) model. The performance of the suggested control algorithm is validated in the Choreonoid simulator with a model of DRC-HUBO+ [11], [12].

In this paper, a current control scheme for the brushless DC (BLDC) motor is proposed. In order to estimate the phase current, it employs the adaptive extended Kalman filter (EKF) and measurement of a single DC link current. When estimating the motor phase current, measurement of a single DC link current is scaled by PWM (Pulse Width Modulation) duty. If the PWM duty is very small, the sensitivity of the measurement noise is dramatically increased. In order to solve this problem adaptive EKF is applied. Therefore, estimated phase current using adaptive EKF prevents the possible occurrence of an unstable situation due to the sensitivity. The accuracy of the proposed current control scheme was confirmed by comparing the estimated current by adaptive EKF and the measured actual phase current. In additions, the effectiveness was verified through the current-control time response of the when the PWM duty for the control was close to zero. By using the proposed current control scheme, robust current control of the BLDC motor was possible with a single DC link current.

For robots, a flexible approach is very important. Even when the robot is a humanoid, it does not have to perfectly mimic human motion. If necessary, the humanoid robot can adapt to other technologies even when these technologies make it different from humans. In a real environment or a disaster environment, humanoid robots are a good solution to assist humans. However, the stability problem of biped locomotion remains. In this paper, we introduce a new strategy of attaching a wheel to our humanoid robot in order to achieve mobility efficiency with a bipedal walking and wheel driven mode. Additionally, this strategy can enhance the stability. Through the proposed method, the humanoid robot can traverse uneven terrain and climb stairs with a walking motion, and can move safely with wheels on the ground. In addition, a method will be presented that can enhance the performance of wheel movement by using redundant joints and sensors on the humanoid robot. Various experiments and the DARPA Robotics Challenge results validate the efficiency and the feasibility of the proposed strategy.