Physical Human-Robot Interaction (pHRI) is an important field that has grown considerably over the last years. Nowadays, new possible applications are being evaluated. In order to tackle the new issues that might arise, novel methods for robot control have to be used. To ease the comparison and evaluation of those methods, this work proposes a simulated frame-work to study the collaboration between a robot manipulator and a person while moving payloads. The way of conceiving the simulated framework done in Matlab is presented, detailing how the robot, the object, and the person can be described. Experiments are done on a real robot KUKA LBR iiwa 14 R820 to compare and validate the interaction forces predicted by the proposed framework. Results showed that this method allows to simulate the co-manipulation of objects, even with unknown load, showing forces that are close to the real ones applied by the person. The Matlab code is publicly available at https://gitlab.com/MMujica/simulated_framework_phrc.

In modern robotics, the manipulators are no longer isolated under fully controlled conditions but rather conceived to work in unconstrained environments. Under these operations, compliant control and passivity properties of the robot are of great importance, and thus the system’s energy function plays a crucial role in the control design. In this work, we propose a new design of cartesian impedance control for a flexible robot whose dynamics is represented within the port-Hamiltonian framework. To improve the performance of the system and maximize the capabilities of the robot, the robotic control system is enhanced with energy tanks that allow for temporarily non-passive operations, but ensure the passivity of the extended system. In addition, a secondary controller is designed using the port-Hamiltonian approach to cover the case of redundant robotic manipulators. The performance of the full control system is tested via simulations of the Kuka iiwa manipulator in closed loop with the proposed passivity-based controller. The results show a satisfactory performance of the control system for set-point regulation, external forces, time-varying reference trajectories, and parametric uncertainty.

The human-robot collaboration is a promising and challenging field of robotics research. One of the main collaboration tasks is the object co-manipulation where the human and robot are in a continuous physical interaction and forces exerted must be handled. This involves some issues known in robotics as physical Human-Robot Interaction (pHRI), where human safety and interaction comfort are required. Moreover, a definition of interaction quality metrics would be relevant. In the current work, the assessment of Human-Robot object co-manipulation task was explored through the proposed metrics of interaction quality, based on human forces throughout the movement. This analysis is based on co-manipulation of objects with different dynamical properties (weight and inertia), with and without including these properties knowledge in the robot control law. Here, the human is a leader of task and the robot the follower without any information of the human trajectory and movement profile. For the robot control law, a well-known impedance control was applied on a 7-dof Kuka LBR iiwa 14 R820 robot. Results show that the consideration of object dynamical properties in the robot control law is crucial for a good and more comfortable interaction. Besides, human efforts are more significant with a higher no-considered weight, whereas it remains stable when these weights were considered.

This paper focuses on interactive motion planning processes intended to assist a human operator when simulating industrial tasks in Virtual Reality. Such applications need motion planning on surfaces. We propose an original haptic path planning algorithm with contact, H-RRT-C, based on a RRT planner and a real-time interactive approach involving a haptic device for computer-operator authority sharing. Force feedback allows the human operator to keep contact consistently and provides the user with the feel of the contact, and the force applied by the operator on the haptic device is used to control the roadmap extension. Our approach has been validated through two experimental examples, and brings significant improvement over state of the art methods in both free and contact space to solve path-planning queries and contact operations such as insertion or sliding in highly constrained environments.

This work deals with interactive motion planning processes intended to assist a human operator when simulating industrial tasks such as assembly, maintenance or disassembly in Virtual Reality. Such applications need motion planning on surfaces. We propose an original interactive path planning algorithm with contact, I-RRT-C, based on a RRT-Connect approach. This algorithm is based on a real-time interactive approach allowing both an automatic motion planner and a human operator to jointly explore the workspace. A parameter balances the authority between the computer and the operator to reduce processing times. We improve the guidance by allowing to sample on the surfaces of obstacles. Our method allows to find a path in cluttered environments or to solve contact operations such as insertion or sliding tasks. Last, we present experimental results showing that our interactive path planner with contact brings a significant improvement over state of the art methods in both free and contact space.

This work deals with planning processes for the assistance to manipulation in order to simulate industrial tasks such as assembly, maintenance or disassembly in Virtual Reality. This paper presents a novel interactive path planning algorithm with contact based on an BiRRT approach. First, we propose a real-time interactive planner where both a computer and a human operator simultaneously search the workspace therefore largely speeding up the process. An authority sharing parameter can control the autonomy of the computer. Then we present a novel contact-space algorithm able to sample on the surface of obstacles. This method helps finding paths in cluttered environments or solving specific contact tasks such as insertion or sliding operations. We finish by presenting the results of our interactive path planner with contact through three examples showing significant improvement over usual methods in both free and contact space.

This work considers Virtual Reality (VR) applications dealing with objects manipulation (such as industrial product assembly, disassembly or maintenance simulation). For such applications, the operator performing the simulation can be assisted by path planning techniques from the robotics research field. A novel automatic path planner involving geometrical, topological and semantic information of the environment is proposed for the guidance of the user through a haptic device. The interaction allows on one hand, the automatic path planner providing assistance to the human operator, and on the other hand, the human operator to reset the whole planning process suggesting a better suited path. Control sharing techniques are used to improve the assisted manipulation ergonomics by dynamically balancing the automatic path planner authority according to the operator involvement in the task, and by predicting user's intent to integrate it as early as possible in the planning process.

International audience

The most widely used technique for generating whole-body motions on a humanoid robot accounting for various tasks and constraints is inverse kinematics. Based on the task-function approach, this class of methods enables the coordination of robot movements to execute several tasks in parallel and account for the sensor feedback in real time, thanks to the low computation cost. To some extent, it also enables us to deal with some of the robot constraints (e.g., joint limits or visibility) and manage the quasi-static balance of the robot. In order to fully use the whole range of possible motions, this paper proposes extending the task-function approach to handle the full dynamics of the robot multibody along with any constraint written as equality or inequality of the state and control variables. The definition of multiple objectives is made possible by ordering them inside a strict hierarchy. Several models of contact with the environment can be implemented in the framework. We propose a reduced formulation of the multiple rigid planar contact that keeps a low computation cost. The efficiency of this approach is illustrated by presenting several multicontact dynamic motions in simulation and on the real HRP-2 robot.

We are interested in human motion characterization and automatic motion simulation. The apparent redundancy of the humanoid w.r.t its explicit tasks lead to the problem of choosing a plausible movement in the framework of redundant kinematics. This work explores the intrinsic relationships between singular value decomposition at kinematic level and optimization principles at task level and joint level. Two task-based schemes devoted to simulation of human motion are then proposed and analyzed. These results are illustrated by motion captures, analyses and task-based simulations. Pattern of singular values serve as a basis for a discussion concerning the similarity of simulated and real motions.

In this paper, we propose a solution to compute full-dynamic motions for a humanoid robot, accounting for various kinds of constraints such as dynamic balance or joint limits. As a first step, we propose a unification of task-based control schemes, in inverse kinematics or inverse dynamics. Based on this unification, we generalize the cascade of quadratic programs that were developed for inverse kinematics only. Then, we apply the solution to generate, in simulation, whole-body motions for a humanoid robot in unilateral contact with the ground, while ensuring the dynamic balance on a non horizontal surface.

Control methods based on a hierarchy of tasks provide a fast, easily-modifiable, and accurate way of generating a motion. In this paper, we propose to extend this hierarchical approach by using a cascade of quadratic programs to handle simultaneously the robot dynamics, inequality and equality constraints, and multiple non-coplanar unilateral contacts. First, we detail the proposed generic inverse-dynamics solver. Then, we prove that the model used to handle contacts encompasses the classical zero-moment-point balance condition. Finally, as an example of the capabilities of the method, we generate a complex motion where the humanoid robot HRP2 sits down on an armchair, using the armrests as additional contacts, while ensuring joint position and velocity limits.

This paper describes a global interactive framework enabling an automatic path-planner and a user to collaborate for finding a path in cluttered virtual environments. First, a collaborative architecture including the user and the planner is described. Then, for real time purpose, a motion planner divided into different steps is presented. First, a preliminary workspace discretization is done without time limitations at the beginning of the simulation. Then, using these pre-computed data, a second algorithm finds a collision free path in real time. Once the path is found, an haptic artificial guidance on the path is provided to the user. The user can then influence the planner by not following the path and automatically order a new path research. The performances are measured on tests based on assembly simulation in CAD scenes.

This paper describes a global interactive scheme including fast motion planning and real time guiding force for 3D CAD part assembly or disassembly tasks. For real time purpose, the motion planner is divided into different steps. First, a preliminary workspace discretization is done without time limitations at the beginning of the simulation. Then, using those computed data, a second part tries to find a collision free path in real time. Once the path is found, an haptic artificial force is applied constraining the user on the path. The user can then influence the planner by not following the path and automatically order a new path research. The performance of this haptic assistance is measured on a test simulation based on an ALSTOM power components assembly simulation.

Repetitive motion on industrial workstations is at the origin of musculoskeletal disorders (MSD). There is a need for new simulation tools that allows for human motion prediction. This paper addresses the problem of realistic human motion simulation on industrial workstations. It is based on motion analysis and control synthesis on a kinematics basis. Literature and motion captures are compared. Then, a scheme based on optimization in Cartesian and motor space is proposed and tested on 2 significant examples. Singular Value theory is used for determining the shape of hand paths. Finally, an industrial application is simulated. Simulations are realized with a 23 Degrees Of Freedom (DOF) virtual human and are also of interest for humanoid robots.

This work is devoted to planning and execution of complex missions in robotics. Robotics has evolved from an industrial, repetitive framework to application domains with much more variability of tasks, with increasing complexity in uncertain environment. This is clearly the case for service robotics for example, but even industrial robots have now to work in environment not totally calibrated for the task they have to perform. The result is that the classical decomposition in static ordered local tasks cannot apply in presence of such a variability. It has a poor dynamic performance and cannot cope with uncertainties. Our work is organized around a complex mission: "Go to the blackboard and write" for mobile manipulators that have capabilities of locomotion and manipulation. It is a simple and intuitive example of a complex mission that relies on different sensors, exhibits different operating modes and needs to switch between different feedbacks and set-points. Our approach is based on hybrid dynamical systems. It is focused on dynamical sequencing of control laws that ensures good transients, robustness and allows to update the mission at every transition from one mode to another. Simulations have been realized with Matlab Simulink and Stateflow toolboxes and an experimental validation has been developed within the controller on the H/sub 2/bis nonholonomic mobile manipulator.

We propose a systematic modelling of the nonholonomic mobile manipulators built from a robotic arm mounted on a wheeled mobile platform. It extends the fundamental notions of nonholonomy, mobility and maneuverability to the case of these hybrid holonomic/nonholonomic systems. It offers unambiguous definitions and models to the designer of kinematic control laws.

We propose a generic scheme to solve the kinematic control problem of wheeled mobile manipulators when the operational motion is imposed. We generalize the Additional Task Method to solve the control problem of these redundant nonholonomic systems.

We extend the standard definition of manipulability to the case of a nonholonomic mobile manipulator built from an n joint robotic arm and a nonholonomic mobile platform. The effects of mounting the arm on a nonholonomic platform are shown through the analysis of the manipulability thus defined. Applications of criteria inherited from manipulability considerations are given to justify design and to generate the controls of our system.

Deals with path planning for mobile nonholonomic manipulators. The system is composed of a nonholonomic mobile platform and a simple kinematic chain holonomic arm. We propose strategies for planning paths between two points in the generalized and operational spaces. Redundancy and optimization criteria are key elements of the approach. Applications follow for a planar system in the case of point to point tasks.

This paper deals with the optimal control (time optimal) of a mobile robot moving in an unobstructed planar environment. The mobile robot is equipped with two independent acceleration-driven wheels so that accelerations are bounded. Using the mobile robot's configuration known through its position and orientation, the problem consists of determining the optimal control that allows the robot to move between two imposed configurations, the start and arrival taking place at zero velocity. Our approach is based on analytically extracting as much information as possible from the Pontryagin's maximum principle (PMP) before starting a numerical search. The recently reported numerical result, showing that this extremal control which is of "bang-bang" type and only requires four switch times or five sequences, is invalidated. We show a configuration space zone in which no extremal control using five sequences is optimal. We also show that there exist, in a part of this zone, extremal controls requiring seven sequences that are candidates for optimality.

This paper addresses the time-optimal point to point motion problem for rigid manipulators. The goal is to clarify analytical results provided by optimal control theory and the reduction of complexity they induce in a numerical search. The nature of exact and approximate solutions is discussed in the general n-link case. Then, extending results obtained previously, it is shown that a class of two-link rigid manipulators has many properties that are false for generic multi-input affine systems of the same dimensions. Particularly, a great improvement is realized from the complexity viewpoint. The results are of interest for both designing and verifying a numerical method.

Shows how to compute the region of accessibility for a model of a car that moves forwards and backwards with a lower bounded turning radius and a constant velocity. This problem deals with the computation of the shortest paths when the starting configuration i.e., position and direction, is completely specified and the goal is only defined by a position letting free the direction. The authors first exhibit the shortest path for any goal position and show its uniqueness. Then they compute the boundary of the region reachable by such paths. Such regions are useful in motion planning for a nonholonomic mobile robot.

The author considers the structure of solutions in time-optimal point to point motion for rigid manipulators. An analytic approach is presented based on the specific structure of two-link rigid manipulators. Partial results on regularity and the reduction of the number of types of solutions in comparison with the general affine problem are discussed. First, the Hamiltonian form of the dynamic model of manipulators is briefly recalled. The three kinds of candidate controls for general affine systems are presented. Generic properties of n-link manipulators related to their nice Lie-algebraic structure are considered. An original approach based on the existence of a cyclic generalized coordinate is shown to be fruitful and leads to a deeper analysis in the case of two degree-of-freedom (DOF) manipulators.>