Nadia Barbara Figueroa Fernandez

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Humans have a remarkable way of learning, adapting and mastering new manipulation tasks. With the current advances in Machine Learning (ML), the promise of having robots with such capabilities seems to be on the cusp of reality. Transferring human-level sk ...

State-dependent dynamical systems (DSs) offer adaptivity, reactivity, and robustness to perturbations in motion planning and physical human-robot interaction tasks. Learning DS-based motion plans from non-linear reference trajectories is an active research ...

In this paper, we present an approach for learning a neural implicit signed distance function expressed in joint space coordinates, that efficiently computes distance-to-collisions for arbitrary robotic manipulator configurations. Computing such distances ...

Coordination is essential in the design of dynamic control strategies for multi-arm robotic systems. Given the complexity of the task and dexterity of the system, coordination constraints can emerge from different levels of planning and control. Primarily, ...

In this letter, we propose a real-time self-collision avoidance approach for whole-body humanoid robot control. To achieve this, we learn the feasible regions of control in the humanoid's joint space as smooth self-collision boundary functions. Collision-f ...

The use of coordinated multi-arm robotic systems allows to preform manipulations of heavy or bulky objects that would otherwise be infeasible for a single-arm robot. This paper concisely introduces our work on coordinated multi-arm control [Salehian et al. ...

In this work, we introduce a novel Dynamical System (DS)-based approach for modeling complex and compliant manipulation tasks, that are composed of a sequence of action phases with different compliance requirements; i.e. impedance primitives. We adopt a cl ...

In this paper, we present an integrated approach that provides compliant control of an iCub humanoid robot and adaptive reaching, grasping, navigating and co-manipulating capabilities. We use state-dependent dynamical systems (DS) to (i) coordinate and dri ...

In this paper, we propose an asymptotically stable joint-space dynamical system that captures desired behaviors in joint-space while stably converging towards a task-space attractor. To encode joint-space behaviors while meeting the stability criteria, the ...

Coordinated control strategies for multi-robot systems are necessary for tasks that cannot be executed by a single robot. This encompasses tasks where the workspace of the robot is too small or where the load is too heavy for one robot to handle. Using mul ...

In this work, we propose a dynamical system based strategy for establishing a stable contact with convex shaped surfaces during non-contact/contact scenarios. A contact is called stable if the impact occurs only once and the robot remains in contact with t ...

In this work, we propose a data-driven approach for real-time self-collision avoidance in multi-arm systems. The approach consists of modeling the regions in joint-space that lead to collisions via a Self-Collision Avoidance (SCA) boundary and use it as a ...

Nadia Barbara Figueroa Fernandez

Chattez avec Graph Search

From High-Level to Low-Level Robot Learning of Complex Tasks: Leveraging Priors, Metrics and Dynamical Systems

Locally active globally stable dynamical systems: Theory, learning, and experiments

Neural Joint Space Implicit Signed Distance Functions for Reactive Robot Manipulator Control

A Unified Framework for Coordinated Multi-Arm Motion Planning

Real-Time Self-Collision Avoidance in Joint Space for Humanoid Robots

Dynamical System-based Motion Planning for Multi-Arm Systems: Reaching for moving objects

Modeling Compositions of Impedance-based Primitives via Dynamical Systems

A Dynamical System Approach for Adaptive Grasping, Navigation and Co-Manipulation with Humanoid Robots

Learning Augmented Joint-Space Task-Oriented Dynamical Systems:A Linear Parameter Varying and Synergetic Control Approach

Coordinated multi-arm motion planning: Reaching for moving objects in the face of uncertainty (RSS 2016 Best Student Paper Award)

Transitioning with confidence during contact/non-contact scenarios

Multi-Arm Self-Collision Avoidance: A Sparse Solution for a Big Data Problem