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Showing papers on "Humanoid robot published in 2009"


Proceedings ArticleDOI
12 May 2009
TL;DR: The mechatronic design of the autonomous humanoid robot called NAO that is built by the French company Aldebaran-Robotics is presented, which has been designed to be affordable without sacrificing quality and performance.
Abstract: This article presents the mechatronic design of the autonomous humanoid robot called NAO that is built by the French company Aldebaran-Robotics. With its height of 0.57 m and its weight about 4.5 kg, this innovative robot is lightweight and compact. It distinguishes itself from existing humanoids thanks to its pelvis kinematics design, its proprietary actuation system based on brush DC motors, its electronic, computer and distributed software architectures. This robot has been designed to be affordable without sacrificing quality and performance. It is an open and easy-to-handle platform. The comprehensive and functional design is one of the reasons that helped select NAO to replace the AIBO quadrupeds in the 2008 RoboCup standard league.

532 citations


Proceedings ArticleDOI
14 Jun 2009
TL;DR: This work considers a probabilistic model for which the maximum likelihood (ML) trajectory coincides with the optimal trajectory and which reproduces the classical SOC solution and utilizes approximate inference methods that efficiently generalize to non-LQG systems.
Abstract: The general stochastic optimal control (SOC) problem in robotics scenarios is often too complex to be solved exactly and in near real time. A classical approximate solution is to first compute an optimal (deterministic) trajectory and then solve a local linear-quadratic-gaussian (LQG) perturbation model to handle the system stochasticity. We present a new algorithm for this approach which improves upon previous algorithms like iLQG. We consider a probabilistic model for which the maximum likelihood (ML) trajectory coincides with the optimal trajectory and which, in the LQG case, reproduces the classical SOC solution. The algorithm then utilizes approximate inference methods (similar to expectation propagation) that efficiently generalize to non-LQG systems. We demonstrate the algorithm on a simulated 39-DoF humanoid robot.

367 citations


Proceedings ArticleDOI
10 Oct 2009
TL;DR: Men were more likely to donate money to the female robot, while women showed little preference, and subjects tended to rate the robot of the opposite sex as more credible, trustworthy, and engaging.
Abstract: Persuasive Robotics is the study of persuasion as it applies to human-robot interaction (HRI). Persuasion can be generally defined as an attempt to change another's beliefs or behavior. The act of influencing others is fundamental to nearly every type of social interaction. Any agent desiring to seamlessly operate in a social manner will need to incorporate this type of core human behavior. As in human interaction, myriad aspects of a humanoid robot's appearance and behavior can significantly alter its persuasiveness - this work will focus on one particular factor: gender. In the current study, run at the Museum of Science in Boston, subjects interacted with a humanoid robot whose gender was varied. After a short interaction and persuasive appeal, subjects responded to a donation request made by the robot, and subsequently completed a post-study questionnaire. Findings showed that men were more likely to donate money to the female robot, while women showed little preference. Subjects also tended to rate the robot of the opposite sex as more credible, trustworthy, and engaging. In the case of trust and engagement the effect was much stronger between male subjects and the female robot. These results demonstrate the importance of considering robot and human gender in the design of HRI.

333 citations


Proceedings ArticleDOI
01 Feb 2009
TL;DR: How a small minimally expressive humanoid robot KASPAR can assume the role of a social mediator - encouraging children with low functioning autism to interact with the robot, to break their isolation and importantly, to facilitate interaction with other people is investigated.
Abstract: The general context of the work presented in this paper is assistive robotics with our long-term aim to support children with autism This paper is part of the Aurora project that studies ways in which robotic systems can encourage basic communication and social interaction skills in children with autism This paper investigates how a small minimally expressive humanoid robot KASPAR can assume the role of a social mediator - encouraging children with low functioning autism to interact with the robot, to break their isolation and importantly, to facilitate interaction with other people The article provides a case study evaluation of segments of trials where three children with autism, who usually do not interact with other people in their day to day activity, interacted with the robot and with co-present adults A preliminary observational analysis was undertaken which applied, in abbreviated form, certain principles from conversation analysis - notably attention to the context in which the target behaviour occurred The analysis was conducted by a social psychologist with expertise in using conversation analysis to understand interactions involving persons with an ASD The analysis emphasises aspects of embodiment and interaction kinesics and revealed unexpected competencies on the part of the children It showed how the robot served as a salient object mediating and encouraging interaction between the children and co-present adults

288 citations


Journal ArticleDOI
TL;DR: An extension of the method of virtual constraints and hybrid zero dynamics (HZD), a very successful method for planar bipeds, is used in order to simultaneously compute a periodic orbit and an autonomous feedback controller that realizes the orbit, for a 3-D bipedal walking robot.
Abstract: This paper presents three feedback controllers that achieve an asymptotically stable, periodic, and fast walking gait for a 3-D bipedal robot consisting of a torso, revolute knees, and passive (unactuated) point feet. The walking surface is assumed to be rigid and flat; the contact between the robot and the walking surface is assumed to inhibit yaw rotation. The studied robot has 8 DOF in the single support phase and six actuators. In addition to the reduced number of actuators, the interest of studying robots with point feet is that the feedback control solution must explicitly account for the robot's natural dynamics in order to achieve balance while walking. We use an extension of the method of virtual constraints and hybrid zero dynamics (HZD), a very successful method for planar bipeds, in order to simultaneously compute a periodic orbit and an autonomous feedback controller that realizes the orbit, for a 3-D (spatial) bipedal walking robot. This method allows the computations for the controller design and the periodic orbit to be carried out on a 2-DOF subsystem of the 8-DOF robot model. The stability of the walking gait under closed-loop control is evaluated with the linearization of the restricted Poincare map of the HZD. Most periodic walking gaits for this robot are unstable when the controlled outputs are selected to be the actuated coordinates. Three strategies are explored to produce stable walking. The first strategy consists of imposing a stability condition during the search of a periodic gait by optimization. The second strategy uses an event-based controller to modify the eigenvalues of the (linearized) Poincare map. In the third approach, the effect of output selection on the zero dynamics is discussed and a pertinent choice of outputs is proposed, leading to stabilization without the use of a supplemental event-based controller.

287 citations


Journal ArticleDOI
TL;DR: A comprehensive introduction to the design of the minimally expressive robot KASPAR, which is particularly suitable for human--robot interaction studies, and a study in the field of developmental robotics into computational architectures based on interaction histories for robot ontogeny.
Abstract: This paper provides a comprehensive introduction to the design of the minimally expressive robot KASPAR, which is particularly suitable for human--robot interaction studies. A low-cost design with off-the-shelf components has been used in a novel design inspired from a multi-disciplinary viewpoint, including comics design and Japanese Noh theatre. The design rationale of the robot and its technical features are described in detail. Three research studies will be presented that have been using KASPAR extensively. Firstly, we present its application in robot-assisted play and therapy for children with autism. Secondly, we illustrate its use in human--robot interaction studies investigating the role of interaction kinesics and gestures. Lastly, we describe a study in the field of developmental robotics into computational architectures based on interaction histories for robot ontogeny. The three areas differ in the way as to how the robot is being operated and its role in social interaction scenarios. Each will be introduced briefly and examples of the results will be presented. Reflections on the specific design features of KASPAR that were important in these studies and lessons learnt from these studies concerning the design of humanoid robots for social interaction will also be discussed. An assessment of the robot in terms of utility of the design for human--robot interaction experiments concludes the paper.

264 citations


Proceedings ArticleDOI
12 May 2009
TL;DR: An improved modification of the original dynamic movement primitive (DMP) framework is presented, which can generalize movements to new targets without singularities and large accelerations and represent a movement in 3D task space without depending on the choice of coordinate system.
Abstract: Dynamical systems can generate movement trajectories that are robust against perturbations. This article presents an improved modification of the original dynamic movement primitive (DMP) framework by Ijspeert et al [1], [2]. The new equations can generalize movements to new targets without singularities and large accelerations. Furthermore, the new equations can represent a movement in 3D task space without depending on the choice of coordinate system (invariance under invertible affine transformations). Our modified DMP is motivated from biological data (spinal-cord stimulation in frogs) and human behavioral experiments. We further extend the formalism to obstacle avoidance by exploiting the robustness against perturbations: an additional term is added to the differential equations to make the robot steer around an obstacle. This additional term empirically describes human obstacle avoidance. We demonstrate the feasibility of our approach using the Sarcos Slave robot arm: after learning a single placing movement, the robot placed a cup between two arbitrarily given positions and avoided approaching obstacles.

261 citations


Proceedings ArticleDOI
12 May 2009
TL;DR: The development of a new compact soft actuation unit intended to be used in multi degree of freedom and small scale robotic systems such as the child humanoid robot “iCub” is presented.
Abstract: This paper presents the development of a new compact soft actuation unit intended to be used in multi degree of freedom and small scale robotic systems such as the child humanoid robot “iCub” [1]. Compared to the other existing series elastic linear or rotary implementations the proposed design shows high integration density and wider passive deflection. The miniaturization of the newly developed high performance unit was achieved with a use of a new rotary spring module based on a novel arrangement of linear springs.

252 citations


Proceedings ArticleDOI
12 May 2009
TL;DR: A new generation of human symbiotic robot, TWENDY-ONE that has a head, trunk, dual arms with a compact passive mechanism, anthropomorphic dual hands with mechanical softness in joints and skins and an omni-wheeled vehicle is developed.
Abstract: In this paper, we propose a sophisticated design of human symbiotic robots that provide physical supports to the elderly such as attendant care with high-power and kitchen supports with dexterity while securing contact safety even if physical contact occurs with them. First of all, we made clear functional requirements for such a new generation robot, amounting to fifteen items to consolidate five significant functions such as “safety”, “friendliness”, “dexterity”, “high-power” and “mobility”. In addition, we set task scenes in daily life where support by robot is useful for old women living alone, in order to deduce specifications for the robot. Based on them, we successfully developed a new generation of human symbiotic robot, TWENDY-ONE that has a head, trunk, dual arms with a compact passive mechanism, anthropomorphic dual hands with mechanical softness in joints and skins and an omni-wheeled vehicle. Evaluation experiments focusing on attendant care and kitchen supports using TWENDY-ONE indicate that this new robot will be extremely useful to enhance quality of life for the elderly in the near future where human and robot co-exist.

248 citations


Journal ArticleDOI
TL;DR: The work presented extends the Maximum Margin Planning (MMP) framework to admit learning of more powerful, non-linear cost functions, and demonstrates practical real-world performance with three applied case-studies including legged locomotion, grasp planning, and autonomous outdoor unstructured navigation.
Abstract: Programming robot behavior remains a challenging task. While it is often easy to abstractly define or even demonstrate a desired behavior, designing a controller that embodies the same behavior is difficult, time consuming, and ultimately expensive. The machine learning paradigm offers the promise of enabling "programming by demonstration" for developing high-performance robotic systems. Unfortunately, many "behavioral cloning" (Bain and Sammut in Machine intelligence agents. London: Oxford University Press, 1995; Pomerleau in Advances in neural information processing systems 1, 1989; LeCun et al. in Advances in neural information processing systems 18, 2006) approaches that utilize classical tools of supervised learning (e.g. decision trees, neural networks, or support vector machines) do not fit the needs of modern robotic systems. These systems are often built atop sophisticated planning algorithms that efficiently reason far into the future; consequently, ignoring these planning algorithms in lieu of a supervised learning approach often leads to myopic and poor-quality robot performance. While planning algorithms have shown success in many real-world applications ranging from legged locomotion (Chestnutt et al. in Proceedings of the IEEE-RAS international conference on humanoid robots, 2003) to outdoor unstructured navigation (Kelly et al. in Proceedings of the international symposium on experimental robotics (ISER), 2004; Stentz et al. in AUVSI's unmanned systems, 2007), such algorithms rely on fully specified cost functions that map sensor readings and environment models to quantifiable costs. Such cost functions are usually manually designed and programmed. Recently, a set of techniques has been developed that explore learning these functions from expert human demonstration. These algorithms apply an inverse optimal control approach to find a cost function for which planned behavior mimics an expert's demonstration. The work we present extends the Maximum Margin Planning (MMP) (Ratliff et al. in Twenty second international conference on machine learning (ICML06), 2006a) framework to admit learning of more powerful, non-linear cost functions. These algorithms, known collectively as LEARCH (LEArning to seaRCH), are simpler to implement than most existing methods, more efficient than previous attempts at non-linearization (Ratliff et al. in NIPS, 2006b), more naturally satisfy common constraints on the cost function, and better represent our prior beliefs about the function's form. We derive and discuss the framework both mathematically and intuitively, and demonstrate practical real-world performance with three applied case-studies including legged locomotion, grasp planning, and autonomous outdoor unstructured navigation. The latter study includes hundreds of kilometers of autonomous traversal through complex natural environments. These case-studies address key challenges in applying the algorithm in practical settings that utilize state-of-the-art planners, and which may be constrained by efficiency requirements and imperfect expert demonstration.

243 citations


Proceedings ArticleDOI
01 Dec 2009
TL;DR: The design process, mechanical features, and electrical features with specifications of HRP-4C, a humanoid robot with a realistic head and a realistic figure of a human being, are introduced.
Abstract: The development of cybernetic human HRP-4C is presented in this paper. The word “Cybernetic Human” is a coinage for us to explain a humanoid robot with a realistic head and a realistic figure of a human being. HRP-4C stands for Humanoid Robotics Platform-4 (Cybernetic human). Standing 158 [cm] tall and weighting 43 [kg] (including batteries), with the joints and dimensions set to average values for young Japanese females, HRP-4C looks very human-like. This paper introduces the design process, mechanical features, and electrical features with specifications of HRP-4C.

Proceedings ArticleDOI
10 Nov 2009
TL;DR: Choregraphe is a very powerful tool that allows macroscopic connection of high level behaviors to easily develop complex software for this 25 degrees of freedom robot, Nao.
Abstract: In this paper, we present Choregraphe: a graphical environment developed by Aldebaran Robotics for programming its humanoid robot, Nao. Choregraphe is a very powerful tool that allows macroscopic connection of high level behaviors to easily develop complex software for this 25 degrees of freedom robot. But it offers as well the ability to perform fine tuning of complex joint or Cartesian motions. At the lowest level, Choregraphe allows programming in Python.

Proceedings ArticleDOI
10 Oct 2009
TL;DR: This paper investigates solving the inverse kinematics problem and motion planning for dual-arm manipulation and re-grasping tasks by combining a gradient-descent approach in the robot's pre-computed reachability space with random sampling of free parameters.
Abstract: In this paper, we present efficient solutions for planning motions of dual-arm manipulation and re-grasping tasks. Motion planning for such tasks on humanoid robots with a high number of degrees of freedom (DoF) requires computationally efficient approaches to determine the robot's full joint configuration at a given grasping position, i.e. solving the Inverse Kinematics (IK) problem for one or both hands of the robot. In this context, we investigate solving the inverse kinematics problem and motion planning for dual-arm manipulation and re-grasping tasks by combining a gradient-descent approach in the robot's pre-computed reachability space with random sampling of free parameters. This strategy provides feasible IK solutions at a low computation cost without resorting to iterative methods which could be trapped by joint-limits. We apply this strategy to dual-arm motion planning tasks in which the robot is holding an object with one hand in order to generate whole-body robot configurations suitable for grasping the object with both hands. In addition, we present two probabilistically complete RRT-based motion planning algorithms (J+−RRT and IK-RRT) that interleave the search for an IK solution with the search for a collision-free trajectory and the extension of these planners to solving re-grasping problems. The capabilities of combining IK methods and planners are shown both in simulation and on the humanoid robot ARMAR-III performing dual-arm tasks in a kitchen environment.

Journal ArticleDOI
TL;DR: A reference generation algorithm based on the LIPM and moving support foot ZMP references is proposed, and the application of Fourier series approximation simplifies the solution, and it generates a smooth ZMP reference.
Abstract: The control of a biped humanoid is a challenging task due to the hard-to-stabilize dynamics. Walking reference trajectory generation is a key problem. Linear Inverted Pendulum Model (LIPM) and Zero Moment Point (ZMP) Criterion-based approaches in stable walking reference generation are reported. In these methods, generally, the ZMP reference during a stepping motion is kept fixed in the middle of the supporting foot sole. This kind of reference generation lacks naturalness, in that the ZMP in the human walk does not stay fixed, but it moves forward under the supporting foot. This paper proposes a reference generation algorithm based on the LIPM and moving support foot ZMP references. The application of Fourier series approximation simplifies the solution, and it generates a smooth ZMP reference. A simple inverse kinematics-based joint space controller is used for the tests of the developed reference trajectory through full-dynamics 3D simulation. A 12-DOF biped robot model is used in the simulations. Simulation studies suggest that the moving ZMP references are more energy efficient than the ones with fixed ZMP under the supporting foot. The results are promising for implementations.

Proceedings ArticleDOI
12 May 2009
TL;DR: An implementation of fast running motions involving a humanoid robot using a motion generation and a balance control and a human-sized humanoid robot that can run forward at 7.0 [km/h] is presented.
Abstract: The present paper describes an implementation of fast running motions involving a humanoid robot. Two important technologies are described: a motion generation and a balance control. The motion generation is a unified way to design both walking and running and can generate the trajectory with the vertical conditions of the Center Of Mass (COM) in short calculation time. The balance control enables a robot to maintain balance by changing the positions of the contact foot dynamically when the robot is disturbed. This control consists of 1) compliance control without force sensors, in which the joints are made compliant by feed-forward torques and adjustment of gains of position control, and 2) feedback control, which uses the measured orientation of the robot's torso used in the motion generation as an initial condition to decide the foot positions. Finally, a human-sized humanoid robot that can run forward at 7.0 [km/h] is presented.

Proceedings Article
22 Jun 2009
TL;DR: This paper presents a framework called the Stack Of Tasks (SoT) implementing a Generalized Inverted Kinematics, which provides a run-time graph of computational nodes and shows through a case study that this framework allows an efficient integration in nowadays middleware such as CORBA.
Abstract: This paper present a framework called the Stack Of Tasks (SoT) implementing a Generalized Inverted Kinematics. This particular implementation provides a run-time graph of computational nodes. It can be modified through a specifically targeted scripting language. It allows hybrid control scheme necessary for complex robot applications such as a HRP-2 humanoid robot in a collaborative working environment. We also show through a case study that this framework allows an efficient integration in nowadays middleware such as CORBA.

Proceedings ArticleDOI
10 Oct 2009
TL;DR: Two crucial elements to legged locomotion are added, i.e., floating-base inverse dynamics control and predictive force control, and it is shown that these elements increase robustness in face of unknown and unanticipated perturbations.
Abstract: Many critical elements for statically stable walking for legged robots have been known for a long time, including stability criteria based on support polygons, good foothold selection, recovery strategies to name a few. All these criteria have to be accounted for in the planning as well as the control phase. Most legged robots usually employ high gain position control, which means that it is crucially important that the planned reference trajectories are a good match for the actual terrain, and that tracking is accurate. Such an approach leads to conservative controllers, i.e. relatively low speed, ground speed matching, etc. Not surprisingly such controllers are not very robust - they are not suited for the real world use outside of the laboratory where the knowledge of the world is limited and error prone. Thus, to achieve robust robotic locomotion in the archetypical domain of legged systems, namely complex rough terrain, where the size of the obstacles are in the order of leg length, additional elements are required. A possible solution to improve the robustness of legged locomotion is to maximize the compliance of the controller. While compliance is trivially achieved by reduced feedback gains, for terrain requiring precise foot placement (e.g. climbing rocks, walking over pegs or cracks) compliance cannot be introduced at the cost of inferior tracking. Thus, model-based control and - in contrast to passive dynamic walkers - active balance control is required. To achieve these objectives, in this paper we add two crucial elements to legged locomotion, i.e., floating-base inverse dynamics control and predictive force control, and we show that these elements increase robustness in face of unknown and unanticipated perturbations (e.g. obstacles). Furthermore, we introduce a novel line-based COG trajectory planner, which yields a simpler algorithm than traditional polygon based methods and creates the appropriate input to our control system.We show results from both simulation and real world of a robotic dog walking over non-perceived obstacles and rocky terrain. The results prove the effectivity of the inverse dynamics/force controller. The presented results show that we have all elements needed for robust all-terrain locomotion, which should also generalize to other legged systems, e.g., humanoid robots.

Proceedings ArticleDOI
12 May 2009
TL;DR: This video gives an overview of the mobile humanoid robotic system “Rollin' Justin” with special emphasis on mechanical design features, control issues and high-level system capabilities such as human robot interaction.
Abstract: Research on humanoid robots for use in servicing tasks, e.g. fetching and delivery, attracts steadily more interest. With “Rollin' Justin” a mobile robotic system and research platform is presented that allows sophisticated control algorithms and dexterous manipulation. This video gives an overview of the mobile humanoid robotic system “Rollin' Justin” with special emphasis on mechanical design features, control issues and high-level system capabilities such as human robot interaction.

Journal ArticleDOI
TL;DR: This paper reports the applicability of the passivity-based contact force control framework for biped humanoids and shows that a simple impedance controller for supporting the feet or hands allows the robot to adapt to low-friction ground without prior knowledge of the ground friction.
Abstract: This paper reports the applicability of our passivity-based contact force control framework for biped humanoids. We experimentally demonstrate its adaptation to unknown rough terrain. Adaptation to uneven ground is achieved by optimally distributed antigravitational forces applied to preset contact points in a feedforward manner, even without explicitly measuring the external forces or the terrain shape. Adaptation to unknown inclination is also possible by combining an active balancing controller based on the center-of-mass (CoM) measurements with respect to the inertial frame. Furthermore, we show that a simple impedance controller for supporting the feet or hands allows the robot to adapt to low-friction ground without prior knowledge of the ground friction. This presentation includes supplementary experimental videos that show a full-sized biped humanoid robot balancing on uneven ground or time-varying inclination.

Journal ArticleDOI
01 May 2009-Robotica
TL;DR: This paper investigates a two-dimensional simulation model of running with nine bodies powered by external moments at all internal joints and determines model parameters and actuator inputs that lead to fully open-loop stable running motions.
Abstract: This paper demonstrates how numerical optimization techniques can efficiently be used to create self-stable running motions for a human-like robot model. Exploitation of self-stability is considered to be a crucial factor for biological running and might be the key for success to make bipedal and humanoid robots run in the future. We investigate a two-dimensional simulation model of running with nine bodies (trunk, thighs, shanks, feet, and arms) powered by external moments at all internal joints. Using efficient optimal control techniques and stability optimization, we were able to determine model parameters and actuator inputs that lead to fully open-loop stable running motions.

Proceedings ArticleDOI
01 Dec 2009
TL;DR: A real time system, robust to partial occlusions and segmentation errors, that provides full hand pose recognition from markerless data, and the pose representation is rich enough to enable a descriptive human-to-robot mapping.
Abstract: Markerless, vision based estimation of human hand pose over time is a prerequisite for a number of robotics applications, such as Learning by Demonstration (LbD), health monitoring, teleoperation, human-robot interaction. It has special interest in humanoid platforms, where the number of degrees of freedom makes conventional programming challenging. Our primary application is LbD in natural environments where the humanoid robot learns how to grasp and manipulate objects by observing a human performing a task. This paper presents a method for continuous vision based estimation of human hand pose. The method is non-parametric, performing a nearest neighbor search in a large database (100000 entries) of hand pose examples. The main contribution is a real time system, robust to partial occlusions and segmentation errors, that provides full hand pose recognition from markerless data. An additional contribution is the modeling of constraints based on temporal consistency in hand pose, without explicitly tracking the hand in the high dimensional pose space. The pose representation is rich enough to enable a descriptive human-to-robot mapping. Experiments show the pose estimation to be more robust and accurate than a non-parametric method without temporal constraints.

Proceedings ArticleDOI
12 May 2009
TL;DR: A new variable admittance control law is designed that guarantees the stability of the robot during constrained motion and also provides a very intuitive human interaction during human-robot interaction.
Abstract: For physical human-robot interaction, safety and dependability are of utmost importance due to the potential risk a relatively powerful robot poses for human beings. From the control standpoint, it is possible to increase this level of safety by guaranteeing that the robot will never exhibit any unstable behaviour. However, stability is not the only concern in the design of a controller for such a robot. During human-robot interaction, the resulting cooperative motion should be truly intuitive and should not restrict in any way the human performance. For this purpose, we have designed a new variable admittance control law that guarantees the stability of the robot during constrained motion and also provides a very intuitive human interaction. The first characteristic is provided by the design of a stability observer while the other is based on a variable admittance control scheme that uses the force derivative as a way to predict human intention. The stability observer is based on a previous stability investigation of cooperative motion which implies the knowledge of the interaction stiffness. A method to accurately estimate this stiffness online using the data coming from the encoder and from a multi-axis force sensor at the end effector is also provided. The stability and intuitivity of the control law were verified in a user study during a cooperative drawing task with a 3 degree-of-freedom (dof) parallel robot.

Proceedings ArticleDOI
12 May 2009
TL;DR: This paper presents the new 25-DoF humanoid walking robot LOLA, characterized by its lightweight construction, a modular, multi-sensory joint design with brushless motors and an electronics architecture using decentralized joint controllers.
Abstract: This paper presents our new 25-DoF humanoid walking robot LOLA. The goal of our research is to realize a fast, human-like walking motion (target speed: 5 km/h). Furthermore, we want to increase the robot's autonomous, vision-guided walking capabilities. The robot has 25 degrees of freedom, including 7-DoF legs with actively driven toe joints. It is characterized by its lightweight construction, a modular, multi-sensory joint design with brushless motors and an electronics architecture using decentralized joint controllers. Special emphasis was put on an improved mass distribution of the leg apparatus to achieve good dynamic performance. The sensor system comprises absolute angular sensors in all links, two custom-made force/torque sensors in the feet and a high-precision inertial sensor in the upper body. Trajectory generation and control system aim at faster, more flexible, and more robust walking patterns.

Proceedings ArticleDOI
07 Dec 2009
TL;DR: Preliminary results assess the theory on switching behavior modes in dyad collaborative tasks: when reproduced with users which were not instructed to behave in either a follower or a leader mode, the robot switched automatically between the learned leader and follower behaviors.
Abstract: This paper presents the application of a statistical framework that allows to endow a humanoid robot with the ability to perform a collaborative manipulation task with a human operator. We investigate to what extent the dynamics of the motion and the haptic communication process that takes place during physical collaborative tasks can be encapsulated by the probabilistic model. This framework encodes the dataset in a Gaussian Mixture Model, which components represent the local correlations across the variables that characterize the task. A set of demonstrations is performed using a bilateral coupling teleoperation setup; then the statistical model is trained in a pure follower/leader role distribution mode between the human and robot alternatively. The task is reproduced using Gaussian Mixture Regression. We present the probabilistic model and the experimental results obtained on the humanoid platform HRP-2; preliminary results assess our theory on switching behavior modes in dyad collaborative tasks: when reproduced with users which were not instructed to behave in either a follower or a leader mode, the robot switched automatically between the learned leader and follower behaviors.

Proceedings ArticleDOI
10 Nov 2009
TL;DR: This paper presents the mobile full-body humanoid tour guide robot Robotinho, designed and enhanced according to the questionnaires filled out by the people who interacted with the robot at previous public demonstrations.
Abstract: Wheeled tour guide robots have already been deployed in various museums or fairs worldwide. A key requirement for successful tour guide robots is to interact with people and to entertain them. Most of the previous tour guide robots, however, focused more on the involved navigation task than on natural interaction with humans. Humanoid robots, on the other hand, offer a great potential for investigating intuitive, multimodal interaction between humans and machines. In this paper, we present our mobile full-body humanoid tour guide robot Robotinho. We provide mechanical and electrical details and cover perception, the integration of multiple modalities for interaction, navigation control, and system integration aspects. The multimodal interaction capabilities of Robotinho have been designed and enhanced according to the questionnaires filled out by the people who interacted with the robot at previous public demonstrations. We present experiences we have made during experiments in which untrained users interacted with the robot.

Proceedings ArticleDOI
12 May 2009
TL;DR: An overview of the design considerations for a mobile platform and their realizations to transform the formerly table-mounted humanoid upper body system Justin into Rollin' Justin, a fully self-sustaining mobile research platform is given.
Abstract: Research on humanoid robots for use in servicing tasks, e.g. fetching and delivery, attracts steadily more interest. With Rollin' Justin a mobile robotic system and research platform is presented that allows the implementation and demonstration of sophisticated control algorithms and dexterous manipulation. Important problems of service robotics such as mobile manipulation and strategies for using the increased workspace and redundancy in manipulation task can be studied in detail. This paper gives an overview of the design considerations for a mobile platform and their realizations to transform the formerly table-mounted humanoid upper body system Justin into Rollin' Justin, a fully self-sustaining mobile research platform.

Journal ArticleDOI
TL;DR: Results of this study demonstrated participants’ willingness to attribute human roles and tasks to an android, although they did not indicate an overall preference for the robot as a social actor.
Abstract: Humanoid robots’ appearance and behavior provide social cues about their purpose and abilities. However, little is known about how a robot’s gender representation will affect users in everyday home use scenarios. This paper presents the results of a study exploring people’s expectations of humanoid robots, or androids, designed for home use. Results of this study demonstrated participants’ willingness to attribute human roles and tasks to an android, although they did not indicate an overall preference for the robot as a social actor. In addition, following the viewing of video stimulus featuring human-robot interactions, robot gender issues surfaced during open-ended interviews.

Journal ArticleDOI
TL;DR: The presence of a physical, embodied robot enabled more interaction, better drumming and turn-taking, as well as enjoyment of the interaction, especially when the robot used gestures.
Abstract: We present results from an empirical study investigating the effect of embodiment and minimal gestures in an interactive drumming game consisting of an autonomous child-sized humanoid robot (KASPAR) playing with child participants. In this study, each participant played three games with a humanoid robot that played a drum whilst simultaneously making (or not making) head gestures. The three games included the participant interacting with the real robot (physical embodiment condition), interacting with a hidden robot when only the sound of the robot is heard (disembodiment condition; note that the term ‘disembodiment’ is used in this paper specifically to refer to an experimental condition where a physical robot produces the sound cues, but is not visible to the participants), or interacting with a real-time image of the robot (virtual embodiment condition). We used a mixed design where repeated measures were used to evaluate embodiment effects and independent-groups measures were used to study the gestures effects. Data from the implementation of a human‐robot interaction experiment with 66 children are presented, and statistically analyzed in terms of participants’ subjective experiences and drumming performance of the human‐robot pair. The subjective experiences showed significant differences for the different embodiment conditions when gestures were used in terms of enjoyment of the game, and perceived intelligence and appearance of the robot. The drumming performance also differed significantly within the embodiment conditions and the presence of gestures increased these differences significantly. The presence of a physical, embodied robot enabled more interaction, better drumming and turn-taking, as well as enjoyment of the interaction, especially when the robot used gestures. © Koninklijke Brill NV, Leiden and The Robotics Society of Japan, 2009

Journal ArticleDOI
TL;DR: The humanoid robot LOLA, its mechatronic hardware design, simulation and real-time walking control, is presented, characterized by a redundant kinematic configuration with 7-DoF legs, an extremely lightweight design, joint actuators with brushless motors and an electronics architecture using decentralized joint control.
Abstract: In this paper we present the humanoid robot LOLA, its mechatronic hardware design, simulation and real-time walking control. The goal of the LOLA-project is to build a machine capable of stable, autonomous, fast and human-like walking. LOLA is characterized by a redundant kinematic configuration with 7-DoF legs, an extremely lightweight design, joint actuators with brushless motors and an electronics architecture using decentralized joint control. Special emphasis was put on an improved mass distribution of the legs to achieve good dynamic performance. Trajectory generation and control aim at faster, more flexible and robust walking. Center of mass trajectories are calculated in real-time from footstep locations using quadratic programming and spline collocation methods. Stabilizing control uses hybrid position/force control in task space with an inner joint position control loop. Inertial stabilization is achieved by modifying the contact force trajectories.

Proceedings ArticleDOI
10 Oct 2009
TL;DR: This work presents a methodology to generate dynamically stable whole-body motions for a humanoid robot, which are converted from human motion capture data and proposes a simplified human model to obtain a human ZMP trajectory, which is used as a reference Z MP trajectory for the humanoid robot to imitate during the kinematic mapping.
Abstract: This work presents a methodology to generate dynamically stable whole-body motions for a humanoid robot, which are converted from human motion capture data. The methodology consists of the kinematic and dynamical mappings for human-likeness and stability, respectively. The kinematic mapping includes the scaling of human foot and Zero Moment Point (ZMP) trajectories considering the geometric differences between a humanoid robot and a human. It also provides the conversion of human upper body motions using the method in [1]. The dynamic mapping modifies the humanoid pelvis motion to ensure the movement stability of humanoid whole-body motions, which are converted from the kinematic mapping. In addition, we propose a simplified human model to obtain a human ZMP trajectory, which is used as a reference ZMP trajectory for the humanoid robot to imitate during the kinematic mapping. A human whole-body dancing motion is converted by the methodology and performed by a humanoid robot with online balancing controllers.