Alessio Rocchi

WALK‐MAN: A High‐Performance Humanoid Platform for Realistic Environments

In this work, we present WALK-MAN, a humanoid platform that has been developed to operate in realistic unstructured environment, and demonstrate new skills including powerful manipulation, robust balanced locomotion, high-strength capabilities, and physical sturdiness. To enable these capabilities, WALK-MAN design and actuation are based on the most recent advancements of series elastic actuator drives with unique performance features that differentiate the robot from previous state-of-the-art compliant actuated robots. Physical interaction performance is benefited by both active and passive adaptation, thanks to WALK-MAN actuation that combines customized high-performance modules with tuned torque/velocity curves and transmission elasticity for high-speed adaptation response and motion reactions to disturbances. WALK-MAN design also includes innovative design optimization features that consider the selection of kinematic structure and the placement of the actuators with the body structure to maximize the robot performance. Physical robustness is ensured with the integration of elastic transmission, proprioceptive sensing, and control. The WALK-MAN hardware was designed and built in 11 months, and the prototype of the robot was ready four months before DARPA Robotics Challenge (DRC) Finals. The motion generation of WALK-MAN is based on the unified motion-generation framework of whole-body locomotion and manipulation (termed loco-manipulation). WALK-MAN is able to execute simple loco-manipulation behaviors synthesized by combining different primitives defining the behavior of the center of gravity, the motion of the hands, legs, and head, the body attitude and posture, and the constrained body parts such as joint limits and contacts. The motion-generation framework including the specific motion modules and software architecture is discussed in detail. A rich perception system allows the robot to perceive and generate 3D representations of the environment as well as detect contacts and sense physical interaction force and moments. The operator station that pilots use to control the robot provides a rich pilot interface with different control modes and a number of teleoperated or semiautonomous command features. The capability of the robot and the performance of the individual motion control and perception modules were validated during the DRC in which the robot was able to demonstrate exceptional physical resilience and execute some of the tasks during the competition.

A manipulation framework for compliant humanoid COMAN: Application to a valve turning task

With the purpose of achieving a desired interaction performance for our compliant humanoid robot (COMAN), in this paper we propose a semi-autonomous control framework and evaluate it experimentally in a valve turning setup. The control structure consists of various modules and interfaces to identify the valve, locate the robot in front of it and perform the manipulation. The manipulation module implements four motion primitives (Reach, Grasp, Rotate and Disengage) and realizes the corresponding desired impedance profile for each phase to accomplish the task. In this direction, to establish a stable and compliant contact between the valve and the robot hands, while being able to generate the sufficient rotational torques depending on the valves friction, Rotate incorporates a novel dual-arm impedance control technique to plan and realize a task-appropriate impedance profile. Results of the implementation of the proposed control framework are firstly evaluated in simulation studies using Gazebo. Subsequent experimental results highlight the efficiency of the proposed impedance planning and control in generation of the required interaction forces to accomplish the task.

OpenSoT: A whole-body control library for the compliant humanoid robot COMAN

A fundamental aspect of controlling humanoid robots lies in the capability to exploit the whole body to perform tasks. This work introduces a novel whole body control library called OpenSoT. OpenSoT is combined with joint impedance control to create a framework that can effectively generate complex whole body motion behaviors for humanoids according to the needs of the interaction level of the tasks. OpenSoT gives an easy way to implement tasks, constraints, bounds and solvers by providing common interfaces. We present the mathematical foundation of the library and validate it on the compliant humanoid robot COMAN to execute multiple motion tasks under a number of constraints. The framework is able to solve hierarchies of tasks of arbitrary complexity in a robust and reliable way.

Yarp Based Plugins for Gazebo Simulator

This paper presents a set of plugins for the Gazebo simulator that enables the interoperability between a robot, controlled using the YARP framework, and Gazebo itself. Gazebo is an open-source simulator that can handle different Dynamic Engines developed by the Open Source Robotics Foundation. Since our plugins conform with the YARP layer used on the real robot, applications written for our robots, COMAN and iCub, can be run on the simulator with no changes. Our plugins have two main components: a YARP interface with the same API as the real robot interface, and a Gazebo plugin which handles simulated joints, encoders, IMUs, force/torque sensors and synchronization. Different modules and tasks for COMAN and iCub have been developed using Gazebo and our plugins as a testbed before moving to the real robots.

Upper-body impedance control with variable stiffness for a door opening task

The advent of humanoids has brought new challenges in the real-world application. As a part of ongoing efforts to foster functionality of the robot accommodating a real environment, this paper introduces a recent progress on a door opening task with our compliant humanoid, CoMan. We presents a task-prioritized impedance control framework for an upper body system that includes a dual-arm, a waist, two soft hands, and 3D camera. Aimed to create desired responses to open the door, a novel stiffness modulation method is proposed, incorporating a realtime optimization. As a preliminary experiment, a full door-opening scenario (approaching to the door and reaching, grasping, rotating and pulling the door handle) is demonstrated under a semi-autonomous operation with a pilot. The experimental result shows the effectiveness and efficacy of the proposed impedance control approach. Despite of uncertainties from sensory data, the door opening task is successfully achieved and safe and robust interaction is established without creating excessive forces.

A Modular Approach for Remote Operation of Humanoid Robots in Search and Rescue Scenarios

In this work we present a modular, robust and user-friendly Pilot Interface meant to control humanoid robots in rescue scenarios during dangerous missions.

Efficient self-collision avoidance based on focus of interest for humanoid robots

This paper deals with the self-collision avoidance problem for humanoid robots in an efficient way. Self-collision avoidance is introduced as a constraint for each task in a hierarchical Inverse Kinematic (IK) problem. Since the number of link pairs which needs to be updated and checked for self-collision, in every control loop, is large, the novel concept of Self-Collision Avoidance Focus of Interest (SCAFoI) is proposed. SCAFoIs permits to predict and dynamically select the necessary link pairs to be checked online to improve the computation efficiency. For each of the several SCAFoIs, which corresponds to the related pairs of kinematic chains of the whole body, the status of the relative positional relationship is predicted. The prediction is done using a Support Vector Machine (SVM) which is a widely used classifier from the machine learning field. Moreover, techniques are proposed to guarantee and improve the prediction performance of the trained classifier. The effectiveness of the framework is verified using the whole-body motion control library OpenSoT by simulation on the model of the recently developed humanoid robot WALK-MAN.

Stable simulation of underactuated compliant hands

Despite increasing popularity of compliant and underactuated hands, few tools are available for modeling them. Thus, we propose a simulation technique to predict the success of a compliant gripper grasping irregular objects, which could be used in mechanism design as well as grasp planning. The simulator we propose integrates joint compliance simulation with a Boundary Layer Expanded Mesh (BLEM) technique to enhance the stability of contact estimation. We compare the proposed simulator with existing simulators via a set of stability and fidelity criteria, including contact force variation, contact position variation, and contact normal variation. Scores along these criteria are correlated with the simulators accuracy of predicting the success/failure of a given grasp pose and preshape. A test set of 13 grasps, with two compliant underactuated hands were manually generated on 4 objects. Experiments suggest that our simulator leads to improvements in the stability criteria, predictability of grasp success, and reduction of simulation artifacts.

XBotCore: A Real-Time Cross-Robot Software Platform

In this work we introduce XBotCore (Cross-Bot-Core), a light-weight, Real-Time (RT) software platform for EtherCAT-based robots. XBotCore is open-source and is designed to be both an RT robot control framework and a software middleware. It satisfies hard RT requirements, while ensuring 1 kHz control loop even in complex Multi-Degree-Of-Freedom systems. It provides a simple and easy-to-use middleware Application Programming Interface (API), for both RT and non-RT control frameworks. This API is completely flexible with respect to the framework a user wants to utilize. Moreover it is possible to reuse the code written using XBotCore API with different robots (cross-robot feature). In this paper, the XBotCore design and architecture will be described and experimental results on the humanoid robot WALK-MAN [17], developed at the Istituto Italiano di Tecnologia (IIT), will be presented.

Towards variable impedance assembly: The VSA peg-in-hole

This paper shows how an accurate peg-in-hole assembly task can be easily achieved with nothing but cheap position sensors when resourcing to Variable Impedance Actuators (VIA). We present the use of a low-cost Variable Stiffness Torso platform, that consists of two 4-DOF non-planar VSA manipulators, for a peg-in-hole assembly task using both arms. One arm holds the peg and the other holds the hole. The task is accomplished without any force measurement and without calling for parallel-manipulator control techniques, exploiting the intrinsic mechanical elasticity of the actuator units. Indeed, a simple position control scheme is required. Simulations and experimental results are reported.