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Whole body tactile perception via tactile skins offers large benefits for robots in unstructured environments. To fully realize this benefit, tactile systems must support real-time data acquisition over a massive number of tactile sensor elements. We present a novel approach for scalable tactile data acquisition using compressed sensing. We first demonstrate that the tactile data is amenable to compressed...
We study the contact-aware state estimation (CASE) problem, i.e., the problem of estimating the state of an object while it is being actively manipulated by a robot. Several researchers have developed particle filters for this problem. They estimate the state (pose and veocity) of manipulated objects, some physical properties (such as mass and shape), and contact information (such as, gain or loss...
Dynamic system states estimation, such as object pose and contact states estimation, is essential for robots to perform manipulation tasks. In order to make accurate estimation, the state transition model needs to be physically correct. Complementarity formulations of the dynamics are widely used for describing rigid body physical behaviors in the simulation field, which makes it a good state transition...
Model-based approaches to the planning or control of robot locomotion or manipulation requires the solution of complementarity problems that model intermittent contact. Fixed-point iteration is a method of computing fixed points of functions and there are several fixed-point theorems to guarantee the existence of fixed points. With the help of proximal point functions, the complementarity problems...
Interactive rigid body simulation is an important part of many modern computer tools, which no authoring tool nor game engine can do without. Such high‐performance computer tools open up new possibilities for changing how designers, engineers, modelers and animators work with their design problems. This paper is a self contained state‐of‐the‐art report on the physics, the models, the numerical methods and the algorithms used in interactive rigid body simulation all of which have evolved and matured over the past 20 years. Furthermore, the paper communicates the mathematical and theoretical details in a pedagogical manner. This paper is not only a stake in the sand on what has been done, it also seeks to give the reader deeper insights to help guide their future research...
Opening doors is a fundamental skill for mobile robots operating in human environments. In this paper we present an approach to learn a dynamic model of a door from sensor observations and utilize it for effectively swinging the door open to a desired angle. The learned model enables the realization of dynamic door-opening strategies and reduces the complexity of the door opening task. For example,...
In this work, we develop a general solution to a broad class of grasping and manipulation problems that we term as C-SLAM for contact simultaneous localization and modeling, where the robots need to accurately track the motions of the contacted bodies and the locations of contacts, while simultaneously estimating important system parameters, such as body dimensions, masses and friction coefficients...
To plan a robotic task involving intermittent contact, such as an assembly task, it is helpful to be able to simulate the task accurately and efficiently. In the past ten years, the prox formulation of the equations of motion has arisen as a competitive alternative to the well-known linear and nonlinear complementarity problem (LCP and NCP) formulations. In this paper, we compare these two formulations,...
To plan a robotic task involving intermittent contact, such as an assembly task, it is helpful to be able to simulate the task accurately and efficiently. In the past ten years, the prox formulation of the equations of motion has arisen as a competitive alternative to the well-known linear and nonlinear complementarity problem (LCP and NCP) formulations. In this paper, we compare these two formulations,...
Allowing robots to communicate naturally with humans is an important goal for social robotics. Most approaches have focused on building high-level probabilistic cognitive models. However, research in cognitive science shows that people often build common ground for communication with each other by seeking and providing evidence of understanding through behaviors like mimicry. Predictive State Representations...
In this paper, we proposed a new physical simulation method that can model non-convex configuration space. The new method employs a novel contact model that take into account geometry information of objects. It can also be shown that it reduces the work for collision detection routines.
Humans rely on a finely tuned ability to recognize and adapt to socially relevant patterns in their everyday face-to-face interactions. This allows them to anticipate the actions of others, coordinate their behaviors, and create shared meaning—to communicate. Social robots must likewise be able to recognize and perform relevant social patterns, including interactional synchrony, imitation, and particular...
Many robotics tasks require a robot to share the same workspace with humans. In such settings, it is important that the robot performs in such a way that does not cause distress to humans in the workspace. In this paper, we address the problem of designing robot controllers which minimize the stress caused by the robot while performing a given task. We present a novel, data-driven algorithm which...
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