Showing papers on "Humanoid robot published in 2006"

Capture Point: A Step toward Humanoid Push Recovery

Abstract: It is known that for a large magnitude push a human or a humanoid robot must take a step to avoid a fall. Despite some scattered results, a principled approach towards "when and where to take a step" has not yet emerged. Towards this goal, we present methods for computing capture points and the capture region, the region on the ground where a humanoid must step to in order to come to a complete stop. The intersection between the capture region and the base of support determines which strategy the robot should adopt to successfully stop in a given situation. Computing the capture region for a humanoid, in general, is very difficult. However, with simple models of walking, computation of the capture region is simplified. We extend the well-known linear inverted pendulum model to include a flywheel body and show how to compute exact solutions of the capture region for this model. Adding rotational inertia enables the humanoid to control its centroidal angular momentum, much like the way human beings do, significantly enlarging the capture region. We present simulations of a simple planar biped that can recover balance after a push by stepping to the capture region and using internal angular momentum. Ongoing work involves applying the solution from the simple model as an approximate solution to more complex simulations of bipedal walking, including a 3D biped with distributed mass.

YARP: Yet Another Robot Platform:

Abstract: We describe YARP, Yet Another Robot Platform, an open-source project that encapsulates lessons from our experience in building humanoid robots. The goal of YARP is to minimize the effort devoted to infrastructure-level software development by facilitating code reuse, modularity and so maximize research-level development and collaboration. Humanoid robotics is a "bleeding edge" field of research, with constant flux in sensors, actuators, and processors. Code reuse and maintenance is therefore a significant challenge. We describe the main problems we faced and the solutions we adopted. In short, the main features of YARP include support for inter-process communication, image processing as well as a class hierarchy to ease code reuse across different hardware platforms. YARP is currently used and tested on Windows, Linux and QNX6 which are common operating systems used in robotics.

Policy Gradient Methods for Robotics

Abstract: The acquisition and improvement of motor skills and control policies for robotics from trial and error is of essential importance if robots should ever leave precisely pre-structured environments. However, to date only few existing reinforcement learning methods have been scaled into the domains of high-dimensional robots such as manipulator, legged or humanoid robots. Policy gradient methods remain one of the few exceptions and have found a variety of applications. Nevertheless, the application of such methods is not without peril if done in an uninformed manner. In this paper, we give an overview on learning with policy gradient methods for robotics with a strong focus on recent advances in the field. We outline previous applications to robotics and show how the most recently developed methods can significantly improve learning performance. Finally, we evaluate our most promising algorithm in the application of hitting a baseball with an anthropomorphic arm

Dynamic Movement Primitives -A Framework for Motor Control in Humans and Humanoid Robotics

Abstract: Given the continuous stream of movements that biological systems exhibit in their daily activities, an account for such versatility and creativity has to assume that movement sequences consist of segments, executed either in sequence or with partial or complete overlap. Therefore, a fundamental question that has pervaded research in motor control both in artificial and biological systems revolves around identifying movement primitives (a.k.a. units of actions, basis behaviors, motor schemas, etc.). What are the fundamental building blocks that are strung together, adapted to, and created for ever new behaviors? This paper summarizes results that led to the hypothesis of Dynamic Movement Primitives (DMP). DMPs are units of action that are formalized as stable nonlinear attractor systems. They are useful for autonomous robotics as they are highly flexible in creating complex rhythmic (e.g., locomotion) and discrete (e.g., a tennis swing) behaviors that can quickly be adapted to the inevitable perturbations of a dynamically changing, stochastic environment. Moreover, DMPs provide a formal framework that also lends itself to investigations in computational neuroscience. A recent finding that allows creating DMPs with the help of well-understood statistical learning methods has elevated DMPs from a more heuristic to a principled modeling approach. Theoretical insights, evaluations on a humanoid robot, and behavioral and brain imaging data will serve to outline the framework of DMPs for a general approach to motor control in robotics and biology.

Trajectory Free Linear Model Predictive Control for Stable Walking in the Presence of Strong Perturbations

Abstract: A humanoid walking robot is a highly nonlinear dynamical system that relies strongly on contact forces between its feet and the ground in order to realize stable motions, but these contact forces are unfortunately severely limited. Model predictive control, also known as receding horizon control, is a general control scheme specifically designed to deal with such constrained dynamical systems, with the potential ability to react efficiently to a wide range of situations. Apart from the question of computation time which needs to be taken care of carefully (these schemes can be highly computation intensive), the initial question of which optimal control problems should be considered to be solved online in order to lead to the desired walking movements is still unanswered. A key idea for answering to this problem can be found in the ZMP preview control scheme. After presenting here this scheme with a point of view slightly different from the original one, we focus on the problem of compensating strong perturbations of the dynamics of the robot and propose a new linear model predictive control scheme which is an improvement of the original ZMP preview control scheme.

ARMAR-III: An Integrated Humanoid Platform for Sensory-Motor Control

Abstract: In this paper, we present a new humanoid robot currently being developed for applications in human-centered environments In order for humanoid robots to enter human-centered environments, it is indispensable to equip them with manipulative, perceptive and communicative skills necessary for real-time interaction with the environment and humans The goal of our work is to provide reliable and highly integrated humanoid platforms which on the one hand allow the implementation and tests of various research activities and on the other hand the realization of service tasks in a household scenario We introduce the different subsystems of the robot We present the kinematics, sensors, and the hardware and software architecture We propose a hierarchically organized architecture and introduce the mapping of the functional features in this architecture into hardware and software modules We also describe different skills related to real-time object localization and motor control, which have been realized and integrated into the entire control architecture

Development of a new humanoid robot WABIAN-2

Abstract: A new humanoid robot-WABIAN-2- that can be used as a human motion simulator is proposed in this paper. Its trunk is designed in order to permit rotation, and forward, backward, and sideway movement. Further, its arms are designed to support its complete weight when pushing a walk-assist machine. Moreover, it can lean on a walk-assist machine by forearm control using trunk motion. Basic walking experiments with WABIAN-2 are conducted with and without a walk-assist machine, thereby confirming its effectiveness

A Storytelling Robot: Modeling and Evaluation of Human-like Gaze Behavior

Abstract: Engaging storytelling is a necessary skill for humanoid robots if they are to be used in education and entertainment applications Storytelling requires that the humanoid robot be aware of its audience and able to direct its gaze in a natural way In this paper, we explore how human gaze can be modeled and implemented on a humanoid robot to create a natural, human-like behavior for storytelling Our gaze model integrates data collected from a human storyteller and a discourse structure model developed by Cassell and her colleagues for human-like conversational agents (1994) We used this model to direct the gaze of a humanoid robot, Honda's ASIMO, as he recited a Japanese fairy tale using a pre-recorded human voice We assessed the efficacy of this gaze algorithm by manipulating the frequency of ASIMO's gaze between two participants and used pre and post questionnaires to assess whether participants evaluated the robot more positively and did better on a recall task when ASIMO looked at them more We found that participants performed significantly better in recalling ASIMO's story when the robot looked at them more Our results also showed significant differences in how men and women evaluated ASIMO based on the frequency of gaze they received from the robot Our study adds to the growing evidence that there are many commonalities between human-human communication and human-robot communication

Programmable central pattern generators: an application to biped locomotion control

Abstract: We present a system of coupled nonlinear oscillators to be used as programmable central pattern generators, and apply it to control the locomotion of a humanoid robot. Central pattern generators are biological neural networks that can produce coordinated multidimensional rhythmic signals, under the control of simple input signals. They are found both in vertebrate and invertebrate animals for the control of locomotion. In this article, we present a novel system composed of coupled adaptive nonlinear oscillators that can learn arbitrary rhythmic signals in a supervised learning framework. Using adaptive rules implemented as differential equations, parameters such as intrinsic frequencies, amplitudes, and coupling weights are automatically adjusted to replicate a teaching signal. Once the teaching signal is removed, the trajectories remain embedded as the limit cycle of the dynamical system. An interesting aspect of this approach is that the learning is completely embedded into the dynamical system, and does not require external optimization algorithms. We use our system to encapsulate rhythmic trajectories for biped locomotion with a simulated humanoid robot, and demonstrate how it can be used to do online trajectory generation. The system can modulate the speed of locomotion, and even allow the reversal of direction (i.e. walking backwards). The integration of sensory feedback allows the online modulation of trajectories such as to increase the basin of stability of the gaits, and therefore the range of speeds that can be produced

The advisor robot: tracing people's mental model from a robot's physical attributes

Abstract: Humanoid robots offer many physical design choices such as voice frequency and head dimensions We used hierarchical statistical mediation analysis to trace differences in people's mental model of robots from these choices In an experiment, a humanoid robot gave participants online advice about their health We used mediation analysis to identify the causal path from the robot's voice and head dimensions to the participants' mental model, and to their willingness to follow the robot's advice The male robot voice predicted impressions of a knowledgeable robot, whose advice participants said they would follow Increasing the voice's fundamental frequency reduced this effect The robot's short chin length (but not its forehead dimensions) predicted impressions of a sociable robot, which also predicted intentions to take the robot's advice We discuss the use of this approach for designing robots for different roles, when people's mental model of the robot matters

A whole-body control framework for humanoids operating in human environments

Abstract: Tomorrow's humanoids will operate in human environments, where efficient manipulation and locomotion skills, and safe contact interactions are critical design factors We report here our recent efforts into these issues, materialized into a whole-body control framework This framework integrates task-oriented dynamic control and control prioritization allowing to control multiple task primitives while complying with physical and movement-related constraints Prioritization establishes a hierarchy between control spaces, assigning top priority to constraint-handling tasks, while projecting operational tasks in the null space of the constraints, and controlling the posture within the residual redundancy This hierarchy is directly integrated at the kinematic level, allowing the program to monitor behavior feasibility at runtime In addition, prioritization allows us to characterize the dynamic behavior of the individual control primitives subject to the constraints, and to synthesize operational space controllers at multiple levels To complete this framework, we have developed free-floating models of the humanoid and incorporate the associated dynamics and the effects of the resulting support contacts into the control hierarchy As part of a long term collaboration with Honda, we are currently implementing this framework into the humanoid robot Asimo

Does appearance matter in the interaction of children with autism with a humanoid robot

Abstract: This article studies the impact of a robot’s appearance on interactions involving four children with autism. This work is part of the Aurora project with the overall aim to support interaction skills in children with autism, using robots as ‘interactive toys’ that can encourage and mediate interactions. We follow an approach commonly adopted in assistive robotics and work with a small group of children with autism. This article investigates which robot appearances are suitable to encourage interactions between a robot and children with autism. The children’s levels of interaction with and response to different appearances of two types of robots are compared: a small humanoid doll, and a life-sized ‘Theatrical Robot’ (a mime artist behaving like a robot). The small humanoid robot appeared either as a human-like ‘pretty doll’ or as a ‘robot’ with plain features. The Theatrical Robot was presented either as an ordinary human, or with plain clothing and a featureless, masked face. The results of these trials clearly indicate the children’s preference in their initial response for interaction with a plain, featureless robot over the interaction with a human-like robot. In the case of the life-size Theatrical Robot, the response of children towards the plain/robotic robot was notably more social and pro-active. Implications of these results for our work on using robots as assistive technology for children with autism and their possible use in autism research are discussed.

A Humanoid Two-Arm System for Dexterous Manipulation

Abstract: This paper presents a humanoid two-arm system developed as a research platform for studying dexterous two-handed manipulation. The system is based on the modular DLR-Lightweight-Robot-III and the DLR-Hand-II. Two arms and hands are combined with a three degrees-of-freedom movable torso and a visual system to form a complete humanoid upper body. In this paper we present the design considerations and give an overview of the different sub-systems. Then, we describe the requirements on the software architecture. Moreover, the applied control methods for two-armed manipulation and the vision algorithms used for scene analysis are discussed.

CB: A Humanoid Research Platform for Exploring NeuroScience

Abstract: This paper presents a 50 degrees of freedom humanoid robot, CB - Computational Brain. CB is a humanoid robot created for exploring the underlying processing of the human brain while dealing with the real world. We place our investigations within real world contexts, as humans do. In so doing, we focus on utilising a system that is closer to human - in sensing, configuration and performance. The real-time network-based control architecture for the control of all 50 degrees of freedom will be presented. The controller provides full position/velocity/force sensing and control at 1 KHz, allowing us the flexibility in deriving various forms of control schemes. Three aspects of the system are highlighted in this paper: 1) physical power for walking; 2) full-body compliant control - physical interactions; 3) perception and control - visual ocularmotor responses.

Design of Android type Humanoid Robot Albert HUBO

Abstract: To celebrate the 100th anniversary of the announcement of the special relativity theory of Albert Einstein, KAIST HUBO team and Hanson robotics team developed android type humanoid robot Albert HUBO which may be the world's first expressive human face on a walking biped robot. The Albert HUBO adopts the techniques of the HUBO design for Albert HUBO body and the techniques of Hanson robotics for Albert HUBO's head. Its height and weight are 137 cm and 57 Kg. Albert HUBO has 66 DOFs (31 for head motions and 35 for body motions) And head part uses `fubber' materials for smooth artificial skin and 28 servo motors for face movements and 3 servo motors for neck movements are used for generating a full range of facial expressions such as laugh, sadness, angry, surprised, etc. and body is modified with HUBO(KHR-3) introduced in 2004 to join with Albert HUBO's head and 35 DC motors are embedded for imitating various human-like body motions

Interactive humanoid robots for a science museum

Abstract: This paper reports on a field trial with interactive humanoid robots at a science museum where visitors are supposed to study and develop an interest in science. In the trial, each visitor wore an RFID tag while looking around the museum's exhibits. Information obtained from the RFID tags was used to direct the robots' interaction with the visitors. The robots autonomously interacted with visitors via gestures and utterances resembling the free play of children [1]. In addition, they performed exhibit-guiding by moving around several exhibits and explaining the exhibits based on sensor information. The robots were highly evaluated by visitors during the two-month trial. Moreover, we conducted an experiment in the field trial to compare the detailed effects of exhibit-guiding and free-play interaction under three operating conditions. This revealed that the combination of the free-play interaction and exhibit-guiding positively affected visitors' experiences at the science museum.

Human-like walking with knee stretched, heel-contact and toe-off motion by a humanoid robot

Abstract: A humanoid robot, WABIAN-2R, capable of human-like walk with stretched knees and heel-contact and toe-off motions is proposed in this paper. WABIAN-2R has two 1-DOF passive joints in its feet to enable it to bend its toes in steady walking. Further, it has two 6-DOF legs, a 2-DOF pelvis, a 2-DOF trunk, two 7-DOF arms with 3-DOF hands, and a 3-DOF neck. In addition, a new algorithm for generating walking patterns with stretched knees and heel-contact and toe-off motions based on the ZMP criterion is described. In this pattern generation, some parameters of the foot trajectories of a biped robot are optimized by using a genetic algorithm in order to generate a continuous and smooth leg motion. Software simulations and walking experiments are conducted, and the effectiveness of the pattern generation and mechanism of WABIAN-2R, which have the ability to realize more human-like walking styles in a humanoid robot, are confirmed.

Building Robota, a Mini-Humanoid Robot for the Rehabilitation of Children with Autism

Abstract: The Robota project constructs a series of multiple degrees of freedom doll-shaped humanoid robots, whose physical features resemble those of a human baby. The Robota robots have been applied as assistive technologies in behavioral studies with low-functioning children with autism. These studies investigate the potential of using an imitator robot to assess children’s imitation ability and to teach children simple coordinated behaviors. In this paper, we review the recent technological developments that have made the Robota robots suitable for use with children with autism. We critically appraise the main outcomes of two sets of behavioral studies conducted with Robota and discuss how these results inform future development of the Robota robots and generally, robots for the rehabilitation of children with complex developmental disabilities.

Design of the robot-cub (iCub) head

Abstract: This paper describes the design of a robot head, developed in the framework of the RobotCub project. This project goals consists on the design and construction of a humanoid robotic platform, the iCub, for studying human cognition. The final platform would be approximately 90 cm tall, with 23 kg and with a total number of 53 degrees of freedom. For its size, the iCub is the most complete humanoid robot currently being designed, in terms of kinematic complexity. The eyes can also move, as opposed to similarly sized humanoid platforms. Specifications are made based on biological anatomical and behavioral data, as well as tasks constraints. Different concepts for the neck design (flexible, parallel and serial solutions) are analyzed and compared with respect to the specifications. The eye structure and the proprioceptive sensors are presented, together with some discussion of preliminary work on the face design

An integrated approach to inverse kinematics and path planning for redundant manipulators

Abstract: We propose a novel solution to the problem of inverse kinematics for redundant robotic manipulators for the purposes of goal selection for path planning. We unify the calculation of the goal configuration with searching for a path in order to avoid the uncertainties inherent to selecting goal configurations which may be unreachable because they currently lie in components of the free configuration space disconnected from the initial configuration. We adopt workspace heuristic functions that implicitly define goal regions of the configuration space and guide the extension of rapidly-exploring random trees (RRTs), which are used to search for these regions. The algorithm has successfully been used to efficiently plan reaching and grasping motions for a humanoid robot equipped with redundant manipulator arms

Imitation Learning of Dual-Arm Manipulation Tasks in Humanoid Robots

Abstract: In this paper, we deal with imitation learning of arm movements in humanoid robots. Hidden Markov Models (HMM) are used to generalize movements demonstrated to a robot multiple times. They are trained with the characteristic features (key points) of each demonstration. Using the same HMM, key points that are common to all demonstrations are identified; only those are considered when reproducing a movement. We also show how HMM can be used to detect temporal dependencies between both arms in dual-arm tasks. We created a model of the human upper body to simulate the reproduction of dual-arm movements and generate natural-looking joint configurations from tracked hand paths. Results are presented and discussed.

Biped Walking Pattern Generator allowing Auxiliary ZMP Control

Abstract: A biped walking pattern generator which allows an additional ZMP control (auxiliary ZMP) is presented. An auxiliary ZMP is realized by an inverse system added to a pattern generator based on the ZMP preview control. To compensate the effect of the auxiliary ZMP, we apply virtual time shifting of the reference ZMP. As an application of the proposed method, a walking control on uneven terrain is simulated. The simulated robot can walk successfully by changing its walking speed as the side effect of the auxiliary ZMP control.

An analytical method for real-time gait planning for humanoid robots

Abstract: This paper studies real-time gait planning for a humanoid robot. By simultaneously planning the trajectories of the COG (Center of Gravity) and the ZMP (Zero Moment Point), a fast and smooth change of gait can be realized. The change of gait is also realized by connecting the newly calculated trajectories to the current ones. While we propose two methods for connecting two trajectories, i.e. the real-time method and the quasi-real-time one, we show that a stable change of gait can be realized by using the quasi-real-time method even if the change of the step position is significant. The effectiveness of the proposed methods are confirmed by simulation and experiment.

Development of the Face Robot SAYA for Rich Facial Expressions

Abstract: The purpose of this study is to develop an interactive communication system that communicates with human beings emotionally. Since the face and its expressions are the most important role for natural communication, we have been developing a face robot that can express facial expressions similar to human beings. In this study, we show a new type face robot SAYA. All McKibben pneumatic actuators are distributed to the surface of the face like a human muscle in order to improve the structure of the face robot and facial muscle movement (Action unit) for natural facial expressions. Since the bending manner of coil spring might be similar to human cervical vertebra, we developed the new head motion mechanism by using coil spring for realizing human like head motion. In this paper, we describe the structure of face robot SAYA and the way of constructing new neck mechanism. We have confirmed that SAYA has ability to express fine facial expressions.

Recent trends in robot-assisted therapy environments to improve real-life functional performance after stroke

Abstract: Upper and lower limb robotic tools for neuro-rehabilitation are effective in reducing motor impairment but they are limited in their ability to improve real world function. There is a need to improve functional outcomes after robot-assisted therapy. Improvements in the effectiveness of these environments may be achieved by incorporating into their design and control strategies important elements key to inducing motor learning and cerebral plasticity such as mass-practice, feedback, task-engagement, and complex problem solving. This special issue presents nine articles. Novel strategies covered in this issue encourage more natural movements through the use of virtual reality and real objects and faster motor learning through the use of error feedback to guide acquisition of natural movements that are salient to real activities. In addition, several articles describe novel systems and techniques that use of custom and commercial games combined with new low-cost robot systems and a humanoid robot to embody the " supervisory presence" of the therapy as possible solutions to exercise compliance in under-supervised environments such as the home.

Online free walking trajectory generation for biped humanoid robot KHR-3(HUBO)

Abstract: This paper describes an algorithm about online gait trajectory generation method, controller for walking, brief introduction of humanoid robot platform KHR-3 (KAIST Humanoid Robot-3: HUBO) and experimental result. The gait trajectory has continuity, smoothness in varying walking period and stride, and it has simple mathematical form which can be implemented easily. It is tested on the robot with some control algorithms. The gait trajectory algorithm is composed of two kinds of function trajectory. The first one is cycloid function, which is used for ankle position in Cartesian coordinate space. Because this profile is made by superposition of linear and sinusoidal function, it has a property of slow start, fast moving, and slow stop. This characteristics can reduce the over burden at instantaneous high speed motion of the actuator. The second one is 3rd order polynomial function. It is continuous in the defined time interval, easy to use when the boundary condition is well defined, and has standard values of coefficients when the time scale is normalized. Position and velocity values are used for its boundary condition. Controllers mainly use F/T(Force/Torque) sensor at the ankle of the robot as a sensor data, and modify the input position profiles (in joint angle space and Cartesian coordinate space). They are to reduce unexpected external forces such as landing shock, and vibration induced by compliances of the sensors and reduction gears, because they can affect seriously on the walking stability. This trajectory and control algorithm is now on the implementing stage for the free-walking realization of KHR-3. As a first stage of realization, we realized the marking time and forward walking algorithm with variable frequency and stride

Online trajectory generation for omnidirectional biped walking

Abstract: This paper describes the online generation of trajectories for omnidirectional walking on two legs. The gait can be parameterized using walking direction, walking speed, and rotational speed. Our approach has a low computational complexity and can be implemented on small onboard computers. We tested the proposed approach using our humanoid robot Jupp. The competitions in the RoboCup soccer domain showed that omnidirectional walking has advantages when acting in dynamic environments