Teleoperation of humanoid robots enables the integration of the cognitive skills and domain expertise of humans with the physical capabilities of humanoid robots. The operational versatility of humanoid robots makes them the ideal platform for a wide range of applications when teleoperating in a remote environment. However, the complexity of humanoid robots imposes challenges for teleoperation, particularly in unstructured dynamic environments with limited communication. Many advancements have been achieved in the last decades in this area, but a comprehensive overview is still missing. This survey article gives an extensive overview of humanoid robot teleoperation, presenting the general architecture of a teleoperation system and analyzing the different components. We also discuss different aspects of the topic, including technological and methodological advances, as well as potential applications.

This paper presents a humanoid robot HRP-2Kai, which is the improvement version of HRP-2 towards disaster response tasks. HRP-2 stands for a humanoid robotics platform-2, which was developed in phase two of the Japanese national project HRP (Humanoid Robotics Project, from 1998FY to 2002FY), while Kai means improvement in Japanese. In a year of the ninth year from releasing HRP-2, the Great East Japan Earthquake shook Japan on March 11, 2011. Since we reflected on that we were not able to deploy our robots for emergency response at that time, we started a study of the disaster response humanoid robots by improving HRP-2. Improvements are presented with its basic specification in this paper.

We present a biped walking pattern generation based on a new way of system discretization named spatially quantized dynamics (SQD). In SQD, a continuous system is discretized by a constant unit length along the walk direction, and the dynamics is represented by a recurrence formula for a unit length motion, taking variable period for each cycle. Using SQD modelling, we can generate a biped gait by taking three steps; 1) Design a walking pattern only considering kinematics in the sagittal plane, 2) Calculate the ZMP and velocity by optimization of the spatially quantized dynamics, 3) Add hip lateral motion for 3D dynamic balance. It is shown that we can easily generate a biped gait with stretched knees and a gait for large step climbing. The validity of the generated patterns are confirmed by simulations.

Maximum absolute acceleration at impact is widely used for evaluating damage at robot fall. In this paper, we measured the impact acceleration of a life-size humanoid robot when it fell down. The experiment showed that a robot suffered maximum acceleration of over 100G at the impact. To mitigate this we tested an airbag system. Our experiment showed the airbag could reduce the peak acceleration to between 20G and 30G, which is an acceptable level for the most of robot hardware.

We propose a control framework for torque controlled humanoid robots that efficiently minimizes the tracking error in a Quadratic Programming (QP)formulated as multiobjective weighted tasks with constraints. It results in an optimal dynamically-feasible reference that can be tracked robustly, with exponential convergence, without joint torque feedback, in the presence of non modelled torque bias and low-frequency bounded disturbances. This is achieved by introducing integral gains in a Lyapunov-stable torque control, which exploit the passivity properties of the dynamical model of the robot and their effect on the dynamic constraints of the QP solver. The robustness of this framework is demonstrated in simulation by commanding our robot, the HRP-5P, to achieve simultaneously several objectives in the configuration and the Cartesian spaces, in the presence of non-modeled static and kinetic joint friction, as well as an uncertain torque scale.