Gustavo Arechavaleta

Animation planning for virtual characters cooperation

This paper presents an approach to automatically compute animations for virtual (human-like and robot) characters cooperating to move bulky objects in cluttered environments. The main challenge is to deal with 3D collision avoidance while preserving the believability of the agents behaviors. To accomplish the coordinated task, a geometric and kinematic decoupling of the system is proposed. This decomposition enables us to plan a collision-free path for a reduced system, then to animate locomotion and grasping behaviors independently, and finally to automatically tune the animation to avoid residual collisions. These three steps are applied consecutively to synthesize an animation. The different techniques used, such as probabilistic path planning, locomotion controllers, inverse kinematics and path planning for closed kinematic chains are explained, and the way to integrate them into a single scheme is described.

A Passivity-Based Model-Free Force–Motion Control of Underwater Vehicle-Manipulator Systems

A passivity-based model-free control scheme for an underwater fully actuated vehicle-manipulator system (UVMS) in contact tasks is proposed. Orthogonalized motion and force second-order sliding modes are enforced for all time for the redundant noninertial robotic UVMS, including when it is subject to a class of fluid disturbances. To this end, we first determine the constrained dynamics using the quasi-Lagrangian formulation to explicitly characterize hydrodynamic fluid perturbations. Our scheme aims at exploiting the structural properties of Lagrangian systems, then we derive a mapping between the quasi-Lagrangian UVMS to its equivalent Lagrangian form, and study the conditions for open-loop passivity preservation during the interaction of postures and contact constraints between the end effector of the UVMS and the rigid contact surface of bulky objects in cluttered submarine environments. Internal motions are simultaneously computed by solving, in the tangent subspace of the contact manifold, a hierarchy of secondary tasks to satisfy the posture constraints. More importantly, the solution shapes the extended errors that are used to preserve passivity and to enforce dissipativity so as to guarantee local exponential stability without any knowledge of the complex UVMS dynamics, and the energetic performance of the UVMS in closed-loop. Illustrative simulations are discussed to show the feasibility of the proposed scheme.

HUMANOID LOCOMOTION PLANNING FOR VISUALLY GUIDED TASKS

In this work, we propose a landmark-based navigation approach that integrates (1) high-level motion planning capabilities that take into account the landmarks position and visibility and (2) a stack of feasible visual servoing tasks based on footprints to follow. The path planner computes a collision-free path that considers sensory, geometric, and kinematic constraints that are specific to humanoid robots. Based on recent results in movement neuroscience that suggest that most humans exhibit nonholonomic constraints when walking in open spaces, the humanoid steering behavior is modeled as a differential-drive wheeled robot (DDR). The obtained paths are made of geometric primitives that are the shortest in distance in free spaces. The footprints around the path and the positions of the landmarks to which the gaze must be directed are used within a stack-of-tasks (SoT) framework to compute the whole-body motion of the humanoid. We provide some experiments that verify the effectiveness of the proposed strategy on the HRP-2 platform.

Real-time smooth task transitions for hierarchical inverse kinematics

Hierarchical inverse kinematics (HIK) is widely used for generating feasible velocity trajectories that serve as input references for highly redundant robots such as humanoid robots. To generate the velocity trajectories a set of prioritized tasks should be provided. For some applications, it is not necessary to change the priority order of the tasks in the stack of tasks (SoT) along the motion execution. However, complex tasks need a dynamic behavior of the SoT such that the insertion, removal or swap can be performed at running time. These task transitions may induce discontinuities in the joint velocities if they are not carefully handled. In this context, we propose an efficient strategy to manage task transitions through a simple procedure which smoothly interchange the priority of a couple of consecutive prioritized tasks. Furthermore, our method does not increase the computational cost of the HIK since neither any additional task should be added, nor parallel control laws should be computed. As a result our strategy may be used in real time to produce the velocity commands of real humanoid robots. The effectiveness of our strategy is verified at simulation level with the HRP-2 humanoid robot performing complex time-driven tasks.

Mechanical part assembly planning with virtual mannequins

This paper deals with mechanical part assembly planning. The goal is to automatically compute a collision-free path for both the part to be assembled and the mannequin manipulating it. Two approaches are proposed according to the difficulty of the problem. Both are based on a general probabilistic diffusion algorithm working in the configuration space of the considered system. The first approach consists in first planning a path for the part alone and then in checking the feasibility of the solution by adding the mannequin. The second one considers the part grasped and the mannequin as a single system. While the first approach performs quickly the second one is able to solve more constrained and difficult cases. Both solutions are based on the same path planning library allowing the user to easily evaluate the proposed solutions. Experimental results based on feedback experiences in automotive industry are presented

Visual path following using a sequence of target images and smooth robot velocities for humanoid navigation

In this paper, we propose an approach of following a visual path for humanoid navigation. The problem consists in computing appropriate robot velocities for the humanoid walking task from the visual data shared between the current robot view and a set of target images. Two types of visual controllers are evaluated: a position-based scheme and an image-based scheme. Both of them rely on the estimation of the homography model even for non-planar scenes. We assume that the sequence of target images is given and we focus on the controllers performance. Because classical visual path following controllers generate discontinuous robot velocities, we propose a generic controller (applicable for different types of visual feedback) to alleviate this issue, which is a main contribution of the paper. The stability of such controller is addressed theoretically and verified through experiments with a NAO humanoid robot.

Motion planning for a vigilant humanoid robot

This paper presents a motion planner for a vigilant humanoid robot. In this context of surveillance, the robot task is to keep a distinctive point in the environment in sight during all of its motion. The method we propose consists of three main ingredients: (1) A motion planner for an appropriate simplified model of the walking robot, adapted to the particular needs of humanoid robots, that outputs an admissible path with local optimality properties. This path is guaranteed to satisfy the visibility constraints resulting both from the landmark and from the angular limits of the mechanical system; (2) A generic walking pattern generator that produces stable walking motions; (3) A generalized inverse-kinematics module to satisfy the remaining collisions and posture constraints, in particular the gaze direction. The effectiveness of this method is shown with several examples on the humanoid robot plataform HRP-2.

Continuous kinematic control with terminal attractors for handling task transitions of redundant robots

This paper proposes a general scheme based on terminal attractors to parametrize operational tasks with respect to time in continuous kinematic controllers. Commonly, a pseudo-inverse operator is applied to solve operational tasks. However, it is known that discontinuities in the control signals appear as a by-product of task transitions during motion execution. In particular, these transitions involve the insertion, removal and swapping of tasks. Recently, some methods have been reported that overcome such discontinuities in the control signals. In this work, we provide time parametrization capabilities to these continuous kinematic controllers in order to handle the time axis of operational tasks at will. Then, we show that the proposed scheme can be naturally extended for the case of prioritized kinematic tasks while preserving continuity under task transitions. Our scheme is validated in a real experiment with a NAO humanoid robot.

Visual servo walking control for humanoids with finite-time convergence and smooth robot velocities

ABSTRACT In this paper, we address the problem of humanoid locomotion guided from information of a monocular camera. The goal of the robot is to reach a desired location defined in terms of a target image, i.e., a positioning task. The proposed approach allows us to introduce a desired time to complete the positioning task, which is advantageous in contrast to the classical exponential convergence. In particular, finite-time convergence is achieved while generating smooth robot velocities and considering the omnidirectional waking capability of the robot. In addition, we propose a hierarchical task-based control scheme, which can simultaneously handle the visual positioning and the obstacle avoidance tasks without affecting the desired time of convergence. The controller is able to activate or inactivate the obstacle avoidance task without generating discontinuous velocity references while the humanoid is walking. Stability of the closed loop for the two task-based control is demonstrated theoretically even during the transitions between the tasks. The proposed approach is generic in the sense that different visual control schemes are supported. We evaluate a homography-based visual servoing for position-based and image-based modalities, as well as for eye-in-hand and eye-to-hand configurations. The experimental evaluation is performed with the humanoid robot NAO.

Comments on "An Optimality Principle Governing Human Walking

The paper in question [G. Arechavaleta, J. P. Laumond, H. Hicheur, and A. Berthoz, “An optimality principle governing human walking,” IEEE Trans. Robot., vol. 24, no. 1, pp. 5-14, Feb. 2008] suggested that human-walking paths minimize variation in curvature and hence can be approximated by the solution to an optimal control problem. This conclusion was reached by analysis of experimental data based on the maximum principle. We correct two errors in this analysis and consider their consequences.