Nonprehensile Object Transportation with a Legged Manipulator

This paper tackles the problem of nonprehensile object transportation through a legged manipulator. A whole- body control architecture is devised to prevent sliding of the object placed on the tray at the manipulator’s end-effector and retain the legged robot balance during walking. The controller solves a quadratic optimization problem to realize the sought transportation task while maintaining the contact forces between the tray and the object and between the legs and the ground within their respective friction cones, also considering limits on the input torques. An extensive simulation campaign confirmed the feasibility of the approach and evaluated the control performance through a thorough statistical analysis conducted varying mass, friction, and the dimension of the transported object

Task-Oriented Contact Optimization for Pushing Manipulation with Mobile Robots

This work addresses the problem of transporting an object along a desired planar trajectory by pushing with mobile robots. More specifically, we concentrate on establishing optimal contacts between the object and the robots to execute the given task with minimum effort. We present a task-oriented contact placement optimization strategy for object pushing that allows calculating optimal contact points minimizing the amplitude of forces required to execute the task. Exploiting the optimized contact configuration, a motion controller uses the computed contact forces in feed-forward and position error feedback terms to realize the desired trajectory tracking task. Simulations and real experiments results confirm the validity of our approach

Dexterous Grasping by Manipulability Selection for Mobile Manipulator with Visual Guidance

Industry 4.0 demands the heavy usage of robotic mobile manipulators with high autonomy and intelligence. The goal is to accomplish dexterous manipulation tasks without prior knowledge of the object status in unstructured environments. It is important for the mobile manipulator to recognize and detect the objects, determine manipulation pose, and adjust its pose in the workspace fast and accurately. In this research, we developed a stereo vision algorithm for the object pose estimation using point cloud data from multiple stereo vision systems. An improved iterative closest point algorithm method is developed for the pose estimation. With the pose input, algorithms and several criteria are studied for the robot to select and adjust its pose by maximizing its manipulability on a given manipulation task. The performance of each technical module and the complete robotic system is finally shown by the virtual robot in the simulator and real robot in experiments. This study demonstrates a setup of autonomous mobile manipulator for various flexible manufacturing and logistical scenarios

Towards a self-collision aware teleoperation framework for compound robots

This work lays the foundations of a self-collision aware teleoperation framework for compound robots. The need of an haptic enabled system which guarantees self-collision and joint limits avoidance for complex robots is the main motivation behind this paper. The objective of the proposed system is to constrain the user to teleoperate a slave robot inside its safe workspace region through the application of force cues on the master side of the bilateral teleoperation system. A series of simulated experiments have been performed on the Kuka KMRiiwa mobile robot; however, due to its generality, the framework is prone to be easily extended to other robots. The experiments have shown the applicability of the proposed approach to ordinary teleoperation systems without altering their stability properties. The benefits introduced by this framework enable the user to safely teleoperate whichever complex robotic system without worrying about self-collision and joint limitations

Enhancing bilateral teleoperation using camera-based online virtual fixtures generation

In this paper we present an interactive system to enhance bilateral teleoperation through online virtual fixtures generation and task switching. This is achieved using a stereo camera system which provides accurate information of the surrounding environment of the robot and of the tasks that have to be performed in it. The use of the proposed approach aims at improving the performances of bilateral teleoperation systems by reducing the human operator workload and increasing both the implementation and the execution efficiency. In fact, using our method virtual guidances do not need to be programmed a priori but they can be instead automatically generated and updated making the system suitable for unstructured environments. We strengthen the proposed method using passivity control in order to safely switch between different tasks while teleoperating under active constraints. A series of experiments emulating real industrial scenarios are used to show that the switch between multiple tasks can be passively and safely achieved and handled by the system

Vision based virtual fixture generation for teleoperated robotic manipulation

In this paper we present a vision-based system for online virtual fixture generation suitable for manipulation tasks using remote controlled robots. This system makes use of a stereo camera system which provides accurate pose estimation of parts within the surrounding environment of the robot using features detection algorithms. The proposed approach is suitable for fast adaptation of the teleoperation system to different manipulation tasks without the need of tedious reimplementation of virtual constraints. Our main goal is to improve the efficiency of bilateral teleoperation systems by reducing the human operator effort in programming the system. In fact, using this method virtual guidances do not need to be programmed a priori but they can be instead dynamically generated on-the-fly and updated at any time making, in the end, the system suitable for any unstructured environment. In addition, this methodology is easily adaptable to any kind of teleoperation system since it is independent from the used master/slave robots. In order to validate our approach we performed a series of experiments in an emulated industrial scenario. We show how through the use of our approach a generic telemanipulation task can be easily accomplished without influencing the transparency of the system

Enhancing airplane boarding procedure using vision based passenger classification

This paper presents the implementation of a new boarding strategy that exploits passenger and hand-luggage detection and classification to reduce the boarding time onto an airplane. A vision system has the main purpose of providing passengers data, in terms of agility coefficient and hand-luggage size to a seat assignment algorithm. The software is able to dynamically generate the passenger seat that reduces the overall boarding time while taking into account the current airplane boarding state. The motivation behind this work is to speed up of the passenger boarding using the proposed online procedure of seat assignment based on passenger and luggage classification. This method results in an enhancement of the boarding phase, in terms of both time and passenger experience. The main goal of this work is to demonstrate the usability of the proposed system in real conditions proving its performances in terms of reliability. Using a simple hardware and software setup, we performed several experiments recreating a gate entrance mock up and comparing the measurements with ground truth data to assess the reliability of the system

Haptic-Based Shared-Control Methods for a Dual-Arm System

We propose novel haptic guidance methods for a dual-arm telerobotic manipulation system, which are able to deal with several different constraints, such as collisions, joint limits, and singularities. We combine the haptic guidance with shared-control algorithms for autonomous orientation control and collision avoidance meant to further simplify the execution of grasping tasks. The stability of the overall system in various control modalities is presented and analyzed via passivity arguments. In addition, a human subject study is carried out to assess the effectiveness and applicability of the proposed control approaches both in simulated and real scenarios. Results show that the proposed haptic-enabled shared-control methods significantly improve the performance of grasping tasks with respect to the use of classic teleoperation with neither haptic guidance nor shared control

Portable dVRK: an augmented V-REP simulator of the da Vinci Research Kit

The da Vinci Research Kit (dVRK) is a first generation da Vinci robot repurposed as a research platform and coupled with software and controllers developed by research users. An already quite wide community is currently sharing the dVRK (32 systems in 28 sites worldwide). The access to the robotic system for training surgeons and for developing new surgical procedures, tools and new control modalities is still difficult due to the limited availability and high maintenance costs. The development of simulation tools provides a low cost, easy and safe alternative to the use of the real platform for preliminary research and training activities. The Portable dVRK, which is described in this work, is based on a V-REP simulator of the dVRK patient side and endoscopic camera manipulators which are controlled through two haptic interfaces and a 3D viewer, respectively. The V-REP simulator is augmented with a physics engine allowing to render the interaction of new developed tools with soft objects. Full integration in the ROS control architecture makes the simulator flexible and easy to be interfaced with other possible devices. Several scenes have been implemented to illustrate performance and potentials of the developed simulator