Contingent task and motion planning under uncertainty for human–robot interactions

Manipulation planning under incomplete information is a highly challenging task for mobile manipulators. Uncertainty can be resolved by robot perception modules or using human knowledge in the execution process. Human operators can also collaborate with robots for the execution of some difficult actions or as helpers in sharing the task knowledge. In this scope, a contingent-based task and motion planning is proposed taking into account robot uncertainty and human–robot interactions, resulting a tree-shaped set of geometrically feasible plans. Different sorts of geometric reasoning processes are embedded inside the planner to cope with task constraints like detecting occluding objects when a robot needs to grasp an object. The proposal has been evaluated with different challenging scenarios in simulation and a real environment.Postprint (published version

Task planning using physics-based heuristics on manipulation actions

© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In order to solve mobile manipulation problems, the efficient combination of task and motion planning is usually required. Moreover, the incorporation of physics-based information has recently been taken into account in order to plan the tasks in a more realistic way. In the present paper, a task and motion planning framework is proposed based on a modified version of the Fast-Forward task planner that is guided by physics-based knowledge. The proposal uses manipulation knowledge for reasoning on symbolic literals (both in offline and online modes) taking into account geometric information in order to evaluate the applicability as well as feasibility of actions while evaluating the heuristic cost. It results in an efficient search of the state space and in the obtention of low-cost physically-feasible plans. The proposal has been implemented and is illustrated with a manipulation problem consisting of a mobile robot and some fixed and manipulatable objects.Peer ReviewedPostprint (author's final draft

Planning hand-arm grasping motions with human-like appearance

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksFinalista de l’IROS Best Application Paper Award a la 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, ICROS.This paper addresses the problem of obtaining human-like motions on hand-arm robotic systems performing pick-and-place actions. The focus is set on the coordinated movements of the robotic arm and the anthropomorphic mechanical hand, with which the arm is equipped. For this, human movements performing different grasps are captured and mapped to the robot in order to compute the human hand synergies. These synergies are used to reduce the complexity of the planning phase by reducing the dimension of the search space. In addition, the paper proposes a sampling-based planner, which guides the motion planning ollowing the synergies. The introduced approach is tested in an application example and thoroughly compared with other state-of-the-art planning algorithms, obtaining better results.Peer ReviewedAward-winningPostprint (author's final draft

Sampling C-obstacles border using a filtered deterministic sequence

This paper is focused on the sampling process for path planners based on probabilistic roadmaps. The paper first analyzes three sampling sources: the random sequence and two deterministic sequences, Halton and sd(k), and compares them in terms of dispersion, computational efficiency (including the finding of nearest neighbors), and sampling probabilities. Then, based on this analysis and on the recognized success of the Gaussian sampling strategy, the paper proposes a new efficient sampling strategy based on deterministic sampling that also samples more densely near the C-obstacles. The proposal is evaluated and compared with the original Gaussian strategy in both 2D and 3D configuration spaces, giving promising results

Programming assignments to learn how to build a Probabilistic Roadmap Planner

Research in robot motion planning requires the availability of a simulation environment where to test and validate the theoretic contributions. Nevertheless, PhD programs and graduate studies that include robot motion planning courses usually cover the subject only from a theoretical perspective. Therefore, students aiming to focus their research in this line, face the big challenge of developing their own simulation environment. To cope with this problem, this paper proposes the use of a programming framework based on multi-platform open source code, and presents a set of twelve programming assignments to allow students of any robot motion planning course a quick mastering of the basic skills involved, covering from graphical rendering issues to collision detection or graph representations and algorithms

Robots autónomos diestros como co-trabajadores con operarios humanos

Postprint (author's final draft

Aspectos técnicos de los robots co-trabajadores con operadores humanos

La robótica colaborativa, en la que los robots comparten el espacio de trabajo con los humanos e interactúan con ellos, toma un papel cada vez más relevante. En este contexto, el artículo presenta desarrollos realizados en diferentes aspectos técnicos necesarios para que estos robots funcionen adecuadamente y cumplan las expectativas en cuanto a su integración. En particular, se enfatizan las capacidades de planificación autónoma de tareas y movimientos, de manipulación diestra, de manipulación bimanual y de interacción con los humanos. Todos los desarrollos presentados han sido validados experimentalmente, y en el artículo se incluyen ejemplos ilustrativos de los experimentos realizados.Postprint (published version

Determination of seven frictionless fixturing points searching the object surface with a homogeneous deterministic distribution

The paper deals whit the problem of finding a form-closure fixturing of objects modeled whit triangular meshes and considering as quality measure the maximum wrench that the object can resist in any direction. Although a triangular mesh is a polyhedral representation of the object, the number of faces is too large to allow a practical application of existing approaches for polyhedral objects, and therefore some search procedure have to be applied. In the proposed approach the search of contact points is done looking for points directly on the object boundary instead of on the wrench space. In this way, all the object surface is homogeneously considered, while the quality is evaluated in the wrench space. The procedure iteratively looks, using heuristic criteria, for sets of points that improve the quality. The procedure was implemented and some application examples are included in the paper to illustrate the performanc

An adaptative deterministic sequence for sampling-based motion planners

This paper presents a deterministic sequence with good and useful features for sampling-based motion planners, On the one hand, the proposed sequence is able to generate samples over a hierarchical grid structure of the C-space in an incremental low-dispersion manner. On the other hand it allows to locally control the degree of resolution required at each region of the C-space by disabling the generation of mode samples where they are not needed. Therefore, the proposed sequence combines the strength of deterministic sequences (good uniformity coverage), with that of random sequences (adaptive behavior

cRRT*: Planning loosely-coupled motions for multiple mobile robots

The planning of collision-free paths of a team of mobile robots involves many degrees of freedom and therefore the use of sampling-based methods is a good alternative. Among them, the RRT planner has been proposed to cope with optimization problems, and has been proven to be asymptotically optimal. Any optimization function can be defined, although optimization has been usually focused on the traveled distance or on safety, i.e. to find paths of minimum length or maximum clearance. Other constraints to be considered are related to the coordinate movements of the robots, including aspects like keeping a desired formation o having some similar behavior. In this paper we propose the use of an RRT to optimize the traveled distance but subject to a coupled behavior between robots, i.e. it is desired that the robots behave as a group with similar or coordinated movements. To achieve so, a cost function has been defined that evaluates the alignment of the edges of the RRT with the vectors that define the coupling between the motion directions of the robots. The method establishes a compromise between the independence required to avoid obstacles in a flexible way and the desired coupling to behave as a team. The method is illustrated with several examples.Preprin