Andrés Montaño

An on-line coordination algorithm for multi-robot systems

This paper proposes a solution to the problem of coordinating multi-robot systems, which execute individually planned tasks in a shared workspace. The presented approach is a decoupled method that can coordinate the participants robots in on-line mode. The coordination is achieved through the adjustment of the time evolution of each robot along its original planned path according to the movements of the other robots to assure a collision free execution of their tasks. To assess the proposed approach a two robot system was used, and different tests were performed in graphical simulations as well as in real executions. Some examples are presented in the paper.

Planning manipulation movements of a dual-arm system considering obstacle removing

The paper deals with the problem of planning movements of two hand-arm robotic systems, considering the possibility of using the robot hands to remove potential obstacles in order to obtain a free access to grasp a desired object. The approach is based on a variation of a Probabilistic Road Map that does not rule out the samples implying collisions with removable objects but instead classifies them according to the collided obstacle(s), and allows the search of free paths with the indication of which objects must be removed from the work-space to make the path actually valid; we call it Probabilistic Road Map with Obstacles (PRMwO). The proposed system includes a task assignment system that distributes the task among the robots, using for that purpose a precedence graph built from the results of the PRMwO. The approach has been implemented for a real dual-arm robotic system, and some simulated and real running examples are presented in the paper. The paper proposes a motion planner that we call PRM with obstacles (PRMwO).The PRMwO searches for robot paths and simultaneously determines, if necessary, the obstacles to be removed.The approach uses a precedence graph to look for a proper sequence of actions and for the distribution of tasks among the robot arms.The approach has been implemented for a real dual arm system but it is valid for more than two arms.

Object shape reconstruction based on the object manipulation

This paper presents an approach for the object shape reconstruction based on the object manipulation using tactile information and force feedback. The tactile information collected during the manipulation process and the kinematic information of the hand are used to identify points on the surface of the object in contact with the hand and thus allowing the object shape reconstruction. Distance invariants are measured on the reconstructed object shape in order to perform the object identification. The proposed approach was implemented using the Shunck Dexterous Hand (SDH2). Different tests were performed in real executions and some examples are presented in the paper.

Optimization of robot coordination using temporal synchronization

This work presents an optimization method applied to robot coordination using temporal synchronization. The coordination process considers the possibility of using multi-robot systems in which each robot executes individually planned tasks in a shared environment. The coordination process generates a curve in a discretized coordination space that contains the sequence of coordinated configurations of the robots, this curve can be optimized in order to minimize the backward movements of the robots during their path execution. The optimization method was implemented for a two arm robotic system, a comparison between the executions with and without optimization was performed, and two illustrative experiments are presented in this paper.

Getting comfortable hand configurations while manipulating an object

The paper presents an approach to manipulate unknown objects based on tactile information and force feedback. The object manipulation is performed using two fingers of the Shunck Dexterous Hand, which is equipped with tactile sensors on the fingertips. The contact point on each fingertip is modeled using a virtual articulation which adds a virtual degree of freedom to the finger. The approach uses the tactile data and hand kinematics information in order to estimate a grasp quality measure and to make finger adjustments after an initial grasp in order to improve the hand comfort. The approach was implemented in a real sensorized hand, and some examples manipulating different objects are presented in the paper showing the evolution of the resulting quality.

Unknown object manipulation based on tactile information

This work proposes an approach to manipulate unknown objects based on tactile information. The manipulation can have three goals: the optimization of the hand configuration, the optimization of the grasp quality and the optimization of the object configuration. Three different motion strategies are introduced in order to move the fingers trying to deal with each of the three goals. The strategies can be applied independently or combined in a sequential way. The feasibility of the motion strategies was proven in real experimentation using the Schunk Dexterous Hand SDH2.

Manipulation tasks with a dual arm system including obstacles removing

The paper deals with the problem of planning movements of a two-hand system, considering the possibility of using one hand to remove potential obstacles in order to grasp a desired object with the other hand. The approach is based on a Probabilistic Road Map that does not rule out samples implying collisions with removable objects but instead classify them according to the collided obstacle(s), and allows the search of free paths with the indication of which objects must be removed from the workspace to make the path be actually valid. The approach has been implemented and different tests were performed with considering a real two-hand robotic system with one hand in charge of grasping a desired object and the other in charge of removing the potential obstacles. Some running examples both in simulation and a real workcell are presented in the paper using simulations and real experimentations.

Commanding the Object Orientation Using Dexterous Manipulation

This paper presents an approach to change the orientation of a grasped object using dexterous manipulation teleoperated in a very simple way with the commands introduced by an operator using a keyboard. The novelty of the approach lays on a shared control scheme, where the robotic hand uses the tactile and kinematic information to manipulate an unknown object, while the operator decides the direction of rotation of the object without caring about the relation between his commands and the actual hand movements. Experiments were conducted to evaluate the proposed approach with different objects, varying the initial grasp configuration and sequence of actions commanded by the operator.

Manipulation of Unknown Objects to Improve the Grasp Quality Using Tactile Information

This work presents a novel and simple approach in the area of manipulation of unknown objects considering both geometric and mechanical constraints of the robotic hand. Starting with an initial blind grasp, our method improves the grasp quality through manipulation considering the three common goals of the manipulation process: improving the hand configuration, the grasp quality and the object positioning, and, at the same time, prevents the object from falling. Tactile feedback is used to obtain local information of the contacts between the fingertips and the object, and no additional exteroceptive feedback sources are considered in the approach. The main novelty of this work lies in the fact that the grasp optimization is performed on-line as a reactive procedure using the tactile and kinematic information obtained during the manipulation. Experimental results are shown to illustrate the efficiency of the approach.

Robust dexterous telemanipulation following object-orientation commands

Purpose This paper aims to present a procedure to change the orientation of a grasped object using dexterous manipulation. The manipulation is controlled by teleoperation in a very simple way, with the commands introduced by an operator using a keyboard. Design/methodology/approach The paper shows a teleoperation scheme, hand kinematics and a manipulation strategy to manipulate different objects using the Schunk Dexterous Hand (SDH2). A state machine is used to model the teleoperation actions and the system states. A virtual link is used to include the contact point on the hand kinematics of the SDH2. Findings Experiments were conducted to evaluate the proposed approach with different objects, varying the initial grasp configuration and the sequence of actions commanded by the operator. Originality/value The proposed approach uses a shared telemanipulation schema to perform dexterous manipulation; in this schema, the operator sends high-level commands and a local system uses this information, jointly with tactile measurements and the current status of the system, to generate proper setpoints for the low-level control of the fingers, which may be a commercial close one. The main contribution of this work is the mentioned local system, simple enough for practical applications and robust enough to avoid object falls.