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We consider mobile robot navigation in dense human crowds. In particular, we explore two questions. Can we design a navigation algorithm that encourages humans to cooperate with a robot? Would such cooperation improve navigation performance? We address the first question by developing a probabilistic predictive model of cooperative collision avoidance and(More)
We consider the problem of navigating a mobile robot through dense human crowds. We begin by exploring a fundamental impediment to classical motion planning algorithms called the ''freezing robot problem'': once the environment surpasses a certain level of dynamic complexity, the planner decides that all forward paths are unsafe, and the robot freezes in(More)
This paper presents a model based approach to autonomous dexterous manipulation, developed as part of the DARPA Autonomous Robotic Manipulation (ARM) program. The developed autonomy system uses robot, object, and environment models to identify and localize objects, and well as plan and execute required manipulation tasks. Deliberate interaction with objects(More)
This paper develops a method to fuse stereo vision, force-torque sensor, and joint angle encoder measurements to estimate and track the location of a grasped object within the hand. We pose the problem as a hybrid systems estimation problem, where the continuous states are the object 6D pose, finger contact location, wrist-to-camera transform and the(More)
This paper develops an estimation framework for sensor-guided manipulation of a rigid object via a robot arm. Using an unscented Kalman Filter (UKF), the method combines dense range information (from stereo cameras and 3D ranging sensors) as well as visual appearance features and silhouettes of the object and manipulator to track both an object-fixed frame(More)
DISCLAIMER: The information contained in this paper does not represent the official policies, either expressed or implied, of the Defense Advanced Research Projects Agency (DARPA) or the Department of Defense. DARPA does not guarantee the accuracy or reliability of the information in this paper. Executive Summary This paper describes Team Caltech's(More)
We present a real-time system that enables a highly capable dynamic quadruped robot to maintain an accurate 6-DOF pose estimate (better than 0.5m over every 50m traveled) over long distances traversed through complex, dynamic outdoor terrain, during day and night, in the presence of camera occlusion and saturation, and occasional large external(More)
This article presents the hardware design and software algorithms of RoboSimian, a statically stable quadrupedal robot capable of both dexterous manipulation and versatile mobility in difficult terrain. The robot has generalized limbs and hands capable of mobility and manipulation , along with almost fully hemispherical 3D sensing with passive stereo(More)