User Needs, Benefits, and Integration of Robotic Systems in a Space Station Laboratory

The methodology, results and conclusions of all tasks of the User Needs, Benefits, and Integration Study (UNBIS) of Robotic Systems in a Space Station Laboratory are summarized. Study goals included the determination of user requirements for robotics within the Space Station, United States Laboratory. In Task 1, three experiments were selected to determine user needs and to allow detailed investigation of microgravity requirements. In Task 2, a NASTRAN analysis of Space Station response to robotic disturbances, and acceleration measurement of a standard industrial robot (Intelledex Model 660) resulted in selection of two ranges of microgravity manipulation: Level 1 (10-3 to 10-5 G at greater than 1 Hz) and Level 2 (less than equal 10-6 G at 0.1 Hz). This task included an evaluation of microstepping methods for controlling stepper motors and concluded that an industrial robot actuator can perform milli-G motion without modification. Relative merits of end-effectors and manipulators were studied in Task 3 in order to determine their ability to perform a range of tasks related to the three microgravity experiments. An Effectivity Rating was established for evaluating these robotic system capabilities. Preliminary interface requirements for an orbital flight demonstration were determined in Task 4. Task 5 assessed the impact of robotics

A Framework of Hybrid Force/Motion Skills Learning for Robots

Human factors and human-centred design philosophy are highly desired in today’s robotics applications such as human-robot interaction (HRI). Several studies showed that endowing robots of human-like interaction skills can not only make them more likeable but also improve their performance. In particular, skill transfer by imitation learning can increase usability and acceptability of robots by the users without computer programming skills. In fact, besides positional information, muscle stiffness of the human arm, contact force with the environment also play important roles in understanding and generating human-like manipulation behaviours for robots, e.g., in physical HRI and tele-operation. To this end, we present a novel robot learning framework based on Dynamic Movement Primitives (DMPs), taking into consideration both the positional and the contact force profiles for human-robot skills transferring. Distinguished from the conventional method involving only the motion information, the proposed framework combines two sets of DMPs, which are built to model the motion trajectory and the force variation of the robot manipulator, respectively. Thus, a hybrid force/motion control approach is taken to ensure the accurate tracking and reproduction of the desired positional and force motor skills. Meanwhile, in order to simplify the control system, a momentum-based force observer is applied to estimate the contact force instead of employing force sensors. To deploy the learned motion-force robot manipulation skills to a broader variety of tasks, the generalization of these DMP models in actual situations is also considered. Comparative experiments have been conducted using a Baxter Robot to verify the effectiveness of the proposed learning framework on real-world scenarios like cleaning a table

Momentum Control with Hierarchical Inverse Dynamics on a Torque-Controlled Humanoid

Hierarchical inverse dynamics based on cascades of quadratic programs have been proposed for the control of legged robots. They have important benefits but to the best of our knowledge have never been implemented on a torque controlled humanoid where model inaccuracies, sensor noise and real-time computation requirements can be problematic. Using a reformulation of existing algorithms, we propose a simplification of the problem that allows to achieve real-time control. Momentum-based control is integrated in the task hierarchy and a LQR design approach is used to compute the desired associated closed-loop behavior and improve performance. Extensive experiments on various balancing and tracking tasks show very robust performance in the face of unknown disturbances, even when the humanoid is standing on one foot. Our results demonstrate that hierarchical inverse dynamics together with momentum control can be efficiently used for feedback control under real robot conditions.Comment: 21 pages, 11 figures, 4 tables in Autonomous Robots (2015

Actuators for a space manipulator

The robotic manipulator can be decomposed into distinct subsytems. One particular area of interest of mechanical subsystems is electromechanical actuators (or drives). A drive is defined as a motor with an appropriate transmission. An overview is given of existing, as well as state-of-the-art drive systems. The scope is limited to space applications. A design philosophy and adequate requirements are the initial steps in designing a space-qualified actuator. The focus is on the d-c motor in conjunction with several types of transmissions (harmonic, tendon, traction, and gear systems). The various transmissions will be evaluated and key performance parameters will be addressed in detail. Included in the assessment is a shuttle RMS joint and a MSFC drive of the Prototype Manipulator Arm. Compound joints are also investigated. Space imposes a set of requirements for designing a high-performance drive assembly. Its inaccessibility and cryogenic conditions warrant special considerations. Some guidelines concerning these conditions are present. The goal is to gain a better understanding in designing a space actuator