Force control and reaching movements on the icub humanoid robot (original) (raw)
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Proceedings of the 8th Workshop on Performance Metrics for Intelligent Systems - PerMIS '08, 2008
We report about the iCub, a humanoid robot for research in embodied cognition. At 104 cm tall, the iCub has the size of a three and half year old child. It will be able to crawl on all fours and sit up to manipulate objects. Its hands have been designed to support sophisticate manipulation skills. The iCub is distributed as Open Source following the GPL/FDL licenses. The entire design is available for download from the project homepage and repository (http://www.robotcub.org). In the following, we will concentrate on the description of the hardware and software systems. The scientific objectives of the project and its philosophical underpinning are described extensively elsewhere .
To explore development of motor skills for reaching in the iCub robot, we test the capabilities for a neural network controller to learn progressively by locking some degrees of freedom (DOF) of the robot's arm before allowing it to explore the space with more DOF's. We consider exploration and bio-inspired mechanisms can aid in the development of control of the iCub robot arm. Results suggest the advantage of progressive development over an initial full training, also, these pointed out the importance of interaction with the world and the necessity of trial and error occurring in a time lapse for developing of reaching skills.
THE DESIGN OF THE iCub HUMANOID ROBOT
International Journal of Humanoid Robotics, 2012
This article describes the hardware design of the iCub humanoid robot. The iCub is an open-source humanoid robotic platform designed explicitly to support research in embodied cognition. This paper covers the mechanical and electronic design of the first release of the robot. A series upgrades developed for the second version of the robot (iCub2), which are aimed at the improvement of the mechanical and sensing performance, are also described.
A Whole-Body Stack-of-Tasks compliant control for the Humanoid Robot COMAN
2014
A fundamental aspect of controlling humanoid robots is the capability to use the entire body to perform tasks. In this paper we present an ongoing work to add this capability to the compliant humanoid robot COMAN, designed at the Italian Institute of Technology. Our control architecture is composed by a high level, whole-body inverse kinematic solver and a decentralized, low level, joint impedance control. Such architecture allows to regulate impedance using different strategies maintaining a high level of robustness and it has been developed to perform rescue operations in disaster scenarios. Keywords—Whole-Body Control, Humanoid Bipedal Robot, Stack of Tasks, Compliance
A Unified Framework for Whole-Body Humanoid Robot Control with Multiple Constraints and Contacts
Springer Tracts in Advanced Robotics, 2008
Physical interactivity is a major challenge in humanoid robotics. To allow robots to operate in human environments there is a pressing need for the development of control architectures that provide the advanced capabilities and interactive skills needed to effectively interact with the environment and/or the human partner while performing useful manipulation and locomotion tasks. Such architectures must address the robot whole-body control problem in its most general form: task and whole body motion coordination with active force control at contacts, under various constraints, self collision, and dynamic obstacles. In this paper we present a framework that addresses in a unified fashion the whole-body control problem in the context of multi-point multilink contacts, constraints, and obstacles. The effectiveness of this novel formulation is illustrated through extensive robot dynamic simulations conducted in SAI, and the experimental validation of the framework is currently underway on the ASIMO platform.
2009 9th IEEE-RAS International Conference on Humanoid Robots, 2009
We introduce a novel control framework based on a recurrent neural network for reaching movement generation. The network first learns forward and inverse kinematics, i.e. to associate end effector coordinates with joint angles, by means of attractor states. Modulating the attractor states with the desired target input allows generalization of the learned kinematics to a wide range of untrained target positions. Representing the static kinematic mapping within a dynamical system enables smooth trajectory generation by exploiting the transient network dynamics when approaching an attractor state. Efficient online learning and execution of the network makes the proposed approach real-time capable. We evaluate the network's generalization abilities and controller properties systematically in a humanoid robot setting.
DForC: A real-time method for reaching, tracking and obstacle avoidance in humanoid robots
2012 12th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2012), 2012
We present the Dynamic Force Field Controller (DForC), a reliable and effective framework in the context of humanoid robotics for real-time reaching and tracking in presence of obstacles. It is inspired by well established works based on artificial potential fields, providing a robust basis for sidestepping a number of issues related to inverse kinematics of complex manipulators. DForC is composed of two layers organized in descending order of abstraction: (1) at the highest level potential fields are employed to outline on the fly collisionfree trajectories that serve to drive the robot end-effector toward fixed or moving targets while accounting for obstacles; (2) at the bottom level an optimization algorithm is exploited in place of traditional techniques that resort to the Transposed or Pseudo-Inverse Jacobian, in order to deal with constraints specified in the joints space and additional conditions related to the robot structure. As demonstrated by experiments conducted on the iCub robot, our method reveals to be particularly flexible with respect to environmental changes allowing for a safe tracking procedure, and generating reliable paths in practically every situation.
A Framework For Humanoid Control and Intelligence
2003
One of the goals of humanoid research is the development of a humanoid capable of performing useful tasks in unknown or un- predictable environments. To address the complexities of this task, the robot must continually accumulate and utilize new control and percep- tual knowledge. In this paper, we present a control framework for accom- plishing this. Robot control policies can
ARMAR-III: An integrated humanoid platform for sensory-motor control
2006
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 humancentered 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.
Domo: a force sensing humanoid robot for manipulation research
2004
Humanoid robots found in research and commercial use today typically lack the ability to operate in unstructured and unknown environments. Force sensing and compliance at each robot joint can allow the robot to safely act in these environments. However, these features can be difficult to incorporate into robot designs. We present a new force sensing and compliant humanoid under development in the Humanoid Robotics Group at MIT CSAIL. The robot, named Domo, is to be a research platform for exploring issues in general dexterous manipulation, visual perception, and learning. This project is currently in the design and development phase. In this paper we describe aspects of the design, detail proposed research directions for the robot, and illustrate how the design of humanoid robots can be informed by the desired research goals.