Motion Control of the Hybrid Wheeled-Legged Quadruped Robot Centauro

Emerging applications will demand robots to deal with a complex environment, which lacks the structure and predictability of the industrial workspace. Complex scenarios will require robot complexity to increase as well, as compared to classical topologies such as fixed-base manipulators, wheeled mobile platforms, tracked vehicles, and their combinations. Legged robots, such as humanoids and quadrupeds, promise to provide platforms which are flexible enough to handle real world scenarios; however, the improved flexibility comes at the cost of way higher control complexity. As a trade-off, hybrid wheeled-legged robots have been proposed, resulting in the mitigation of control complexity whenever the ground surface is suitable for driving. Following this idea, a new hybrid robot called Centauro has been developed inside the Humanoid and Human Centered Mechatronics lab at Istituto Italiano di Tecnologia (IIT). Centauro is a wheeled-legged quadruped with a humanoid bi-manual upper-body. Differently from other platform of similar concept, Centauro employs customized actuation units, which provide high torque outputs, moderately fast motions, and the possibility to control the exerted torque. Moreover, with more than forty motors moving its limbs, Centauro is a very redundant platform, with the potential to execute many different tasks at the same time. This thesis deals with the design and development of a software architecture, and a control system, tailored to such a robot; both wheeled and legged locomotion strategies have been studied, as well as prioritized, whole-body and interaction controllers exploiting the robot torque control capabilities, and capable to handle the system redundancy. A novel software architecture, made of (i) a real-time robotic middleware, and (ii) a framework for online, prioritized Cartesian controller, forms the basis of the entire work

XBot: A Cross-Robot Software Framework for Real-Time Control

The widespread use of robotics in new application domains outside the industrial workplace settings requires robotic systems which demonstrate functionalities far beyond that of classical industrial robotic machines. The implementation of these capabilities inevitably increases the complexity of the robotic hardware, control a and software components. This chapter introduces the XBot software architecture for robotics, which is capable of Real-Time (RT) performance with minimum jitter at relatively high control frequency while demonstrating enhanced flexibility and abstraction features making it suitable for the control of robotic systems of diverse hardware embodiment and complexity. A key feature of the XBot is its cross-robot compatibility, which makes possible the use of the framework on different robots, without code modifications, based only on a set of configuration files. The design of the framework ensures easy interoperability and built-in integration with other existing software tools for robotics, such as ROS, YARP or OROCOS, thanks to a robot agnostic API called XBotInterface. The framework has been successfully used and validated as a software infrastructure for collaborative robotic arms as KUKA lbr iiwa/lwr 4+ and Franka Emika Panda, other than humanoid robots such as WALK-MAN and COMAN+, and quadruped centaur-like robots as CENTAURO

Multi-contact planning and control for humanoid robots: Design and validation of a complete framework

In this paper, we consider the problem of generating appropriate motions for a torque- controlled humanoid robot that is assigned a multi-contact loco-manipulation task, i.e., a task that requires the robot to move within the environment by repeatedly establishing and breaking multiple, non-coplanar contacts. To this end, we present a complete multi-contact planning and control framework for multi-limbed robotic systems, such as humanoids. The planning layer works offline and consists of two sequential modules: first, a stance planner computes a sequence of feasible contact combinations; then, a whole-body planner finds the sequence of collision-free humanoid motions that realize them while respecting the physical limitations of the robot. For the challenging problem posed by the first stage, we propose a novel randomized approach that does not require the specification of pre-designed potential contacts or any kind of pre-computation. The control layer produces online torque commands that enable the humanoid to execute the planned motions while guaranteeing closed-loop balance. It relies on two modules, i.e., the stance switching and reactive balancing module; their combined action allows it to withstand possible execution inaccuracies, external disturbances, and modeling uncertainties. Numerical and experimental results obtained on COMAN+, a torque-controlled humanoid robot designed at Istituto Italiano di Tecnologia, validate our framework for loco-manipulation tasks of different complexity

Omnidirectional Walking Pattern Generator Combining Virtual Constraints and Preview Control for Humanoid Robots

This paper presents a novel omnidirectional walking pattern generator for bipedal locomotion combining two structurally different approaches based on the virtual constraints and the preview control theories to generate a flexible gait that can be modified on-line. The proposed strategy synchronizes the displacement of the robot along the two planes of walking: the zero moment point based preview control is responsible for the lateral component of the gait, while the sagittal motion is generated by a more dynamical approach based on virtual constraints. The resulting algorithm is characterized by a low computational complexity and high flexibility, requisite for a successful deployment to humanoid robots operating in real world scenarios. This solution is motivated by observations in biomechanics showing how during a nominal gait the dynamic motion of the human walk is mainly generated along the sagittal plane. We describe the implementation of the algorithm and we detail the strategy chosen to enable omnidirectionality and on-line gait tuning. Finally, we validate our strategy through simulation experiments using the COMAN + platform, an adult size humanoid robot developed at Istituto Italiano di Tecnologia. Finally, the hybrid walking pattern generator is implemented on real hardware, demonstrating promising results: the WPG trajectories results in open-loop stable walking in the absence of external disturbances

XBotCore: A Real-Time Cross-Robot Software Platform

Muratore L, Laurenzi A, Hoffman EM, Rocchi A, Caldwell DG, Tsagarakis NG. XBotCore: A Real-Time Cross-Robot Software Platform. In: IEEE International Conference on Robotic Computing, IRC17. 2017

Balancing Control through Post-Optimization of Contact Forces

International audienceIn this work we present a novel method to address the balancing problem for torque controlled legged robots through post-optimization of contact forces. The main concept consists in treating a legged robot as a fully actuated fixed-base system in order to compute the desired joint torques according to [1]. The under-actuated component of the obtained torques is then be mapped into contact forces through an optimal distribution problem. Besides extending [1] to the floating-base case, the proposed method has the notable advantage of avoiding the specification of a desired momentum of rotation, in addition to a reduced number of decision variables compared to full-inverse dynamics methods. The effectiveness of our approach has been validated in simulation using two different humanoid platforms: the CENTAURO and the COMAN+ robots, both recently developed at Istituto Italiano di Tecnologia (IIT). Preliminary experimental results on COMAN+ are also presented

CartesI/O: A ROS Based Real-Time Capable Cartesian Control Framework

International audienceThis work introduces a framework for the Carte-sian control of multi-legged, highly redundant robots. The proposed framework allows the untrained user to perform complex motion tasks with robotics platforms by leveraging a simple, auto-generated ROS-based interface. Contrary to other motion control frameworks (e.g. ROS MoveIt!), we focus on the execution of Cartesian trajectories that are specified online, rather than planned in advance, as it is the case, for instance, in tele-operation and locomotion tasks. Moreover, we address the problem of generating such motions within a hard real-time (RT) control loop. Finally, we demonstrate the capabilities of our framework both on the COMAN+ humanoid robot, and on the hybrid wheeled-legged quadruped CENTAURO

Locomotion Adaptation in Heavy Payload Transportation Tasks with the Quadruped Robot CENTAURO

International audienceThis paper presents a reactive legged locomotion generation scheme that enables our quadruped robot CEN-TAURO to adapt to varying payloads while walking. The center-of-mass (CoM) trajectories are generated in real time in a model predictive control (MPC) fashion, trading off large stability margins against evenly stretched legs. Vertexbased zero-moment-point (ZMP) constraints are imposed to ensure quasi-static walking stability. A Kalman filter is then implemented to estimate the CoM states and the impact of external payloads which can vary online and affect/disturb the locomotion differently. The CoM estimation is used to update the MPC motion planner at every replanning instant so that the robot can react to unknown and time-varying payloads on the fly. We validate the proposed scheme through experimental trials where the robot walks on flat ground or steps on different surface levels while carrying heavy payloads. It is shown that the proposed reactive locomotion strategy enables the robot to carry 20 kg payloads, which is close to the maximum capacity of the robot arms