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This paper describes a collection of optimization algorithms for achieving dynamic planning, control, and state estimation for a bipedal robot designed to operate reliably in complex environments. To make challenging locomotion tasks tractable, we describe several novel applications of convex, mixed-integer, and sparse nonlinear optimization to problems(More)
One of the most pressing issues with petascale analysis is the transport of simulation results data to a meaningful analysis. Traditional workflow prescribes storing the simulation results to disk and later retrieving them for analysis and visualization. However, at petascale this storage of the full results is prohibitive. A solution to this problem is to(More)
The DARPA Robotics Challenge Trials held in December 2013 provided a landmark demonstration of dexterous mobile robots executing a variety of tasks aided by a remote human operator using only data from the robot’s sensor suite transmitted over a constrained, fieldrealistic communications link. We describe the design considerations, architecture,(More)
Operating a high degree of freedom mobile manipulator, such as a humanoid, in a field scenario requires constant situational awareness, capable perception modules, and effective mechanisms for interactive motion planning and control. A well-designed operator interface presents the operator with enough context to quickly carry out a mission and the(More)
For humanoid robots to fulfill their mobility potential they must demonstrate reliable and efficient locomotion over rugged and irregular terrain. In this paper we present the perception and planning algorithms which have allowed a humanoid robot to use only passive stereo imagery (as opposed to actuating a laser range sensor) to safely plan footsteps to(More)
We introduce a novel open-source framework for analyzing and exploring point cloud datasets and algorithms. This is done by integrating the Point Cloud Library (PCL) within ParaView, a parallel scientific visualization tool. In particular, we demonstrate that by wrapping PCL algorithms as VTK1 filters, we can leverage PCL’s functionality in an interactive,(More)
To approximately quantify the quality of the data generated by our pipeline, and the speed of labeling, 2 we compared with a traditional technique of labeling one image with a polygon of the segmented 3 object (Figure 1). We randomly chose two images from our dataset, and used [1] to label them by 4 hand. A side-by-side comparison of the human labeling and(More)
Deep neural network (DNN) architectures have been shown to outperform traditional pipelines for object segmentation and pose estimation using RGBD data, but the performance of these DNN pipelines is directly tied to how representative the training data is of the true data. Hence a key requirement for employing these methods in practice is to have a large(More)