Towards stratified model-based environmental visual perception for humanoid robots

An autonomous environmental visual perception approach for humanoid robots is presented. The proposed framework exploits the available model information and the context acquired during global localization by establishing a vision-model coupling in order to overcome the limitations of purely data-driven approaches in object recognition and surrounding status assertion. The exploitation of the model-vision coupling through the properceptive components is the key element to solve complex visual assertion-queries with proficient performance. An experimental evaluation with the humanoid robot ARMAR-IIIa is presented.     

Intelligent proximal-policy-optimization-based decision-making system for humanoid robots

With the advancements in technology, robots have gradually replaced humans in different aspects. Allowing robots to handle multiple situations simultaneously and perform different actions depending on the situation has since become a critical topic. Currently, training a robot to perform a designated action is considered an easy task. However, when a robot is required to perform actions in different environments, both resetting and retraining are required, which are time-consuming and inefficient. Therefore, allowing robots to autonomously identify their environment can significantly reduce the time consumed. How to employ machine learning algorithms to achieve autonomous robot learning has formed a research trend in current studies. In this study, to solve the aforementioned problem, a proximal policy optimization algorithm was used to allow a robot to conduct self-training and select an optimal gait pattern to reach its destination successfully. Multiple basic gait patterns were selected, and information-maximizing generative adversarial nets were used to generate gait patterns and allow the robot to choose from numerous gait patterns while walking. The experimental results indicated that, after self-learning, the robot successfully made different choices depending on the situation, verifying this approach’s feasibility.     

A dynamic simulator for humanoid robots

Computer simulation is an essential step in the design and construction of various mechanical structures, including biped robots, because it enables rapid testing and virtual prototyping during the construction phase. Although many different simulators are available, this article gives an overview and a motivation for building a new dynamic multibody simulator. The simulator is especially adapted to humanoid robot Archie, developed at the IHRT Institute at the Technical University of Vienna. In addition, it is shown how the simulator can be used not only in the controller design, but also in the online control loop to extend the available sensors: a virtual sensors principle. This work was presented in part at the First European Workshop on Artificial Life and Robtics, Vienna, Austria, July 12–13, 2007     

类人足球机器人决策系统的设计

类人机器人足球比赛是机器人足球比赛的最高赛事.类人足球机器人的决策系统是基于独立视觉的自主决策系统,很大程度上决定着比赛的胜败.介绍了自主研发的类人足球机器人决策系统的架构及实现方法,并在此基础上运用有限状态机理论,对单个机器人的自主进攻策略进行了详细分析和研究,真实环境中的实验及比赛结果证明了其有效性.该决策系统的设计及研究工作对基于自主决策的多智能体协作以及服务性机器人决策系统的研究都具有重要的价值.     

Cooperative transportation system for humanoid robots using simulation-based learning

In this paper, an approach to the behavior acquisition required for humanoid robots to carry out a cooperative transportation task is proposed. In the case of object transportation involving two humanoid robots, mutual position shifts may occur due to the body swinging of the robots. Therefore, it is necessary to correct the position in real-time. Developing the position shift correction system requires a great deal of effort. Solution to the problem of learning the required behaviors is obtained by using the Classifier System and Q-Learning. The successful cooperation of two HOAP-1 humanoid robots in the transportation task has been confirmed by several experimental results.     

A new artificial life body: biologically inspired dynamic bipedal humanoid robots

Recently, a biologically inspired, bipedal, dynamic, humanoid robot was developed at the Artificial Life and Robotics Laboratory of Oita University. This bipedal humanoid robot is able to walk dynamically and to go up and down stairs. The central pattern generator developed produces various types of walking pattern. This robot has a pair of small CMOS color CCD cameras, a speaker, and a microphone in the head part, and will have a GPS, a portable telephone, and other sensors in the body part, so that the integration of locomotion and behavior to achieve specific demonstrations will be realized. This project develops dynamic mobility and the ability for autonomous recognition and navigation using the biological central nervous system, the brain system, and the real-time control system. Also, the design principles that demonstrate the dynamic interaction between neural and mechanical controls will be clarified. In Phase I, the platform of a small, bipedal, humanoid robot is used to develop autonomous locomotion and autonomous sensing and navigation. In Phase II of the project, an iteration on the platform design for human-size, bipedal, humanoid robots will be performed for operational testing. The development of bipedal humanoid robots that capture biological systems with unique principles and practices could dramatically increase their performance in tasks for national security needs.This work was presented in part at the 8th International Symposium on Artificial Life and Robotics, Oita, Japan, January 24–26, 2003     

Clock-turning gait synthesis for humanoid robots

Turning gait is a basic motion for humanoid robots. This paper presents a method for humanoid tuming, i.e. clock-turning. The objective of clock-turning is to change robot direction at a stationary spot. The clock-turning planning consists of four steps： ankle trajectory generation, hip trajectory generation, knee trajectory generation, and inverse kinematics calculation. Our proposed method is based on a typical humanoid structure with 12 DOFs （degrees of freedom）. The final output of clock-turning planning is 12 reference trajectories, which are used to control a humanoid robot with 12 DOFs. ZMP （zero moment point） is used as stability criterion for the planning. Simulation experiments are conducted to verify the effectiveness of our proposed clock-turuing method.     

A combined approach for improving humanoid robots autonomous cognitive capabilities

Recent technologies advancements promise to change our lives dramatically in the near future. A new different living society is progressively emerging, witnessed from the conception of novel digital ecosystems, where humans are expected to share their own spaces and habits with machines. Humanoid robots are more and more being developed and provided with enriched functionalities; however, they are still lacking in many ways. One important goal in this sense is to enrich their cognitive capabilities, to make them more “intelligent” in order to better support humans in both daily and special activities. The goal of this research is to set a step in bridging the gap between symbolic AI and connectionist approaches in the context of knowledge acquisition and conceptualization. Hence, we present a combined approach based on semantics and machine learning techniques for improving robots cognitive capabilities. This is part of a wider framework that covers several aspects of knowledge management, from representation and conceptualization, to acquisition, sharing and interaction with humans. Our focus in this work is in particular on the development and implementation of techniques for knowledge acquisition. Such techniques are discussed and validated through experiments, carried out on a real robotic platform, showing the effectiveness of our approach. The results obtained confirmed that the combination of the approaches gives superior performance with respect to when they are considered individually.

     

Reflexive stability control framework for humanoid robots

In this paper we propose a general control framework for ensuring stability of humanoid robots, determined through a normalized zero-moment-point (ZMP). The proposed method is based on the modified prioritized kinematic control, which allows smooth and continuous transition between priorities. This, as long as the selected criterion is met, allows arbitrary joint movement of a robot without any regard of the consequential movement of the ZMP. On the other hand, it constrains the movement when the criterion approaches a critical condition. The critical condition thus triggers a reflexive, subconscious behavior, which has a higher priority than the desired, conscious movement. The transition between the two is smooth and reversible. Furthermore, the switching is encapsulated in a single modified prioritized task control equation. We demonstrate the properties of the algorithm on two human-inspired robots developed in our laboratory; a human-inspired leg-robot used for imitating human movement and a skiing robot.     

Self-modeling in humanoid soccer robots

In this paper we discuss the applicability, potential benefits, open problems and expected contributions that an emerging set of self-modeling techniques might bring on the development of humanoid soccer robots. The idea is that robots might continuously generate, validate and adjust physical models of their sensorimotor interaction with the world. These models are exploited for adapting behavior in simulation, enhancing the learning skills of a robot with the regular transference of controllers developed in simulation to reality. Moreover, these simulations can be used to aid the execution of complex sensorimotor tasks, speed up adaptation and enhance task planning. We present experiments on the generation of behaviors for humanoid soccer robots using the Back-to-Reality algorithm. General motivations are presented, alternative algorithms are discussed and, most importantly, directions of research are proposed.     

仿人机器人的机械结构设计与控制系统构建

文章研发了一款适用于机器人教育教学的多功能、多用途、普适性的19自由度的小型仿人机器人,主要完成了该机器人的机械结构设计与控制系统构建工作[1]。所设计的机器人机械结构可靠性高、工艺性好、结构紧凑、样式新颖;所构建的机器人控制系统鲁棒性高、稳定性好、控制准确、反应迅速,圆满地实现了预期的设计任务。通过对优缺点的综合对比,得出组合式构型方案在功能性、实用性和稳定性等方面具有明显优势,有望通过后续软件系统的开发提高其运动效能,真正在青少年机器人教育中发挥重要作用[2]。     

Stepping over obstacles with humanoid robots

The wide potential applications of humanoid robots require that the robots can walk in complex environments and overcome various obstacles. To this end, we address the problem of humanoid robots stepping over obstacles in this paper. We focus on two aspects, which are feasibility analysis and motion planning. The former determines whether a robot can step over a given obstacle, and the latter discusses how to step over, if feasible, by planning appropriate motions for the robot. We systematically examine both of these aspects. In the feasibility analysis, using an optimization technique, we cast the problem into global optimization models with nonlinear constraints, including collision-free and balance constraints. The solutions to the optimization models yield answers to the possibility of stepping over obstacles under some assumptions. The presented approach for feasibility provides not only a priori knowledge and a database to implement stepping over obstacles, but also a tool to evaluate and compare the mobility of humanoid robots. In motion planning, we present an algorithm to generate suitable trajectories of the feet and the waist of the robot using heuristic methodology, based on the results of the feasibility analysis. We decompose the body motion of the robot into two parts, corresponding to the lower body and upper body of the robot, to meet the collision-free and balance constraints. This novel planning method is adaptive to obstacle sizes, and is, hence, oriented to autonomous stepping over by humanoid robots guided by vision or other range finders. Its effectiveness is verified by simulations and experiments on our humanoid platform HRP-2.     

A momentum-based balance controller for humanoid robots on non-level and non-stationary ground

Recent research suggests the importance of controlling rotational dynamics of a humanoid robot in balance maintenance and gait. In this paper, we present a novel balance strategy that controls both linear and angular momentum of the robot. The controller’s objective is defined in terms of the desired momenta, allowing intuitive control of the balancing behavior of the robot. By directly determining the ground reaction force (GRF) and the center of pressure (CoP) at each support foot to realize the desired momenta, this strategy can deal with non-level and non-stationary grounds, as well as different frictional properties at each foot-ground contact. When the robot cannot realize the desired values of linear and angular momenta simultaneously, the controller attributes higher priority to linear momentum at the cost of compromising angular momentum. This creates a large rotation of the upper body, reminiscent of the balancing behavior of humans. We develop a computationally efficient method to optimize GRFs and CoPs at individual foot by sequentially solving two small-scale constrained linear least-squares problems. The balance strategy is demonstrated on a simulated humanoid robot under experiments such as recovery from unknown external pushes and balancing on non-level and moving supports.     

Whole-body hierarchical motion and force control for humanoid robots

Robots acting in human environments usually need to perform multiple motion and force tasks while respecting a set of constraints. When a physical contact with the environment is established, the newly activated force task or contact constraint may interfere with other tasks. The objective of this paper is to provide a control framework that can achieve real-time control of humanoid robots performing both strict and non strict prioritized motion and force tasks. It is a torque-based quasi-static control framework, which handles a dynamically changing task hierarchy with simultaneous priority transitions as well as activation or deactivation of tasks. A quadratic programming problem is solved to maintain desired task hierarchies, subject to constraints. A generalized projector is used to quantitatively regulate how much a task can influence or be influenced by other tasks through the modulation of a priority matrix. By the smooth variations of the priority matrix, sudden hierarchy rearrangements can be avoided to reduce the risk of instability. The effectiveness of this approach is demonstrated on both a simulated and a real humanoid robot.     

Biomimetic pupils for augmenting eye emulation in humanoid robots

Contemporary approaches in the development of humanoid robots continually neglect holistic nuances, particularly in ocular prosthetic design. The standard solid glass and acrylic eye construction techniques implemented in humanoid robot design present the observer with an inaccurate representation of the natural human eye by utilising hardened synthetic materials which prohibit pupillary dynamics. Precise eye emulation is an essential factor in the development of a greater realistic humanoid robot as misrepresentation in ocular form and function will appear distinctly prevalent during proximity face to face communication as eye contact is the primary form of interpersonal communicative processing. This paper explores a new material approach in the development of a more accurate humanoid robotic eye construction by employing natural compounds similar in structure to that found in the organic human eye to replace the traditional glass and acrylic modelling techniques. Furthermore, this paper identifies a gap in current ocular system design as no robotic eye model can accurately replicate all the natural operations of the human iris simultaneously in reaction to light and emotive responsivity. This paper offers a new system design approach to augment future humanoid robot eye construction towards achieving a greater accurate and naturalistic eye emulation.     

Evolutionary design of Sugeno-type fuzzy systems for modelling humanoid robots

An evolutionary design of Sugeno-type fuzzy systems for modelling humanoid robots is presented in this article, and issues related to the determination of the antecedent and consequent structures of the fuzzy model are addressed. In the design of the fuzzy model, determination of the type, the number of membership functions assigned to the input variables, the types of consequent equations for the fuzzy rules, the optimal number of input variables, and the dominant input variables among the input candidates are carried out using evolutionary algorithms. Using these algorithms, proper structures are evolved for the antecedent and the consequent of the Sugeno-type fuzzy model. Simulations are performed to show the effectiveness of the developed method when applied to a humanoid robot system with strong nonlinearities that have 10 input candidates.     

A novel compound biped locomotion algorithm for humanoid robots to realize biped walking

In this paper, a compound biped locomotion algorithm for a humanoid robot under development is presented. This paper is organized in two main parts. In the first part, it mainly focuses on the structural design for the humanoid. In the second part, the compound biped locomotion algorithm is presented based on the reference motion and reference Zero Moment Point （ZMP）. This novel algorithm includes calculation of the upper body motion and trajectory of the Center of Gravity （COG） of the robot. First, disturbances from the environment are eliminated by the compensational movement of the upper body; then based on the error between a reference ZMP and the real ZMP as well as the relation between ZMP and CoG, the CoG error is calculated, thus leading to the CoG trajectory. Then, the motion of the robot converges to its reference motion, generating stable biped walking. Because the calculation of upper body motion and trajectory of CoG both depend on the reference motion, they can work in parallel, thus providing double insurances against the robot＇s collapse. Finally, the algorithm is validated by different kinds of simulation experiments.     

Current-pressure-position triple-loop feedback control of electro-hydrostatic actuators for humanoid robots

To overcome the tradeoff between torque density and response of the backdrivable actuators, actuation by electro-hydrostatic actuators (EHA) is effective. While their backdrivability and energy efficiency was shown in the previous studies, their closed-loop dynamic behavior was not discussed in detail. In this paper, we present the analysis and experimental evaluation of the force control performance of the electro-hydrostatic actuator for the humanoid robot ‘Hydra’. We first present a simplified model of EHA and show that EHA can be simplified as a mass-spring-damper model if all values such as pump torque/velocity and fluid pressure/flow-rate are expressed in the equivalent value seen from the actuator. We also show the comparison between the model and experimentally acquired open-loop dynamic behavior. Then, the evaluation on the force measurement and control performance is shown. The static friction on the rod-seal was 0.46% of the maximum piston force, and with additional strain gauge information, the error can be reduced to 0.28% of the maximum force. We also show that our developed EHA has a pressure control bandwidth of 100?Hz in the fixed piston configuration, which is higher than other state-of-the-art series elastic actuators. In the last of paper, the joint level position and torque control performance of Hydra is examined.