LabelFusion: A Pipeline for Generating Ground Truth Labels for Real RGBD Data of Cluttered Scenes

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 set of labeled data for your specific robotic manipulation task, a requirement that is not generally satisfied by existing datasets. In this paper we develop a pipeline to rapidly generate high quality RGBD data with pixelwise labels and object poses. We use an RGBD camera to collect video of a scene from multiple viewpoints and leverage existing reconstruction techniques to produce a 3D dense reconstruction. We label the 3D reconstruction using a human assisted ICP-fitting of object meshes. By reprojecting the results of labeling the 3D scene we can produce labels for each RGBD image of the scene. This pipeline enabled us to collect over 1,000,000 labeled object instances in just a few days. We use this dataset to answer questions related to how much training data is required, and of what quality the data must be, to achieve high performance from a DNN architecture

The Effects of a Political Culture of Fear on Libyan Student’s Perceptions of Leadership

This study analyzes the effects of political culture of fear on perceptions of leader-member exchange (LMX) relationships between student and faculty, and perceptions of the nature of leadership in Libyan universities. Data were collected by survey from 237 students from 7 different Libyan universities. Factor analysis, confirmatory factor analysis (CFA), and structural equation modeling (SEM) were used to analysis the data. The results of this study show that LMX relationship between faculties and students is classified into three factors: professional respect, affect, and loyalty, culture of fear is classified into three factors: fiction, force, and fealty-finance, and leadership items grouped into 6 factors: Charismatic I, Charismatic II, Autocratic, Malevolent, Team Oriented, and Self Protective. According to the structural equation modeling analysis, Culture of fear affects all LMX and 5 leadership factors and LMX affects 5 Leadership factors

Complexity theory and Al Qaeda: Examining complex leadership

Recent events in the world are forcing us to restructure our understanding of leadership and organization. The al- Qaeda organization and its pervasive presence in the world demonstrated first-hand the power of a flexible, moderately coupled network of individuals brought together by a common need and aligned behind an informal and emergent leader. Its structure, which resulted from bottom-up coordination of individuals who voluntarily came together based on common need rather than from top-down hierarchical control, clearly demonstrates the power of a networked system based on relationships and shared vision and mission. To understand this and other types of network organizations, traditional models of leadership and organizational theory may no longer be sufficient, and may perhaps even limit our ability to realize the capabilities and resilience of such organizational forms. To address such limitations, leadership theorists are exhibiting interest in new perspectives on organizing such as complexity theory (Boal et al., in press; Hunt & Ropo, in press; Marion & Uhl-Bien, 2001; McKelvey, in press; Streatfield, 2001). Complexity theory proposes that organizations are complex systems composed of a diversity of agents who interact with and mutually affect one another, leading to spontaneous “bottom-up” emergence of novel behavior (Marion & Uhl-Bien, 2001; Regine & Lewin, 2000). Because of this, leadership in complex systems requires a shift in thinking from traditional “command-and-control” models that focus on control and stifle emergence (McKelvey, in press) to “complex leadership” models (Marion & Uhl-Bien, 2001) that enable interconnectivity and foster dynamic systems behavior and innovation. In this way, complexity theory helps explain organizational behavior relative to the “dynamic swirl” of social and organizational events that influence complex systems and their agents. The purpose of this article is to derive propositions regarding complexity and complex leadership (Marion & Uhl-Bien, 2001) and to illustrate them using the case of al-Qaeda. We will argue that the conditions that led to the emergence of al-Qaeda were conducive to complex leadership, and that complex leadership helps explain the success of this terrorist movement. Although detailed data of the sort needed for rigorous qualitative analysis are obviously unavailable, we believe that the al- Qaeda example is such a powerful illustration of complexity concepts that it merits a nontraditional format for presentation

Leadership in Complex Organizations

This paper asks how complexity theory informs the role of leadership in organizations. Complexity theory is a science of complexly interacting systems; it explores the nature of interaction and adaptation in such systems and how they influence such things as emergence, innovation, and fitness. We argue that complexity theory focuses leadership efforts on behaviors that enable organizational effectiveness, as opposed to determining or guiding effectiveness. Complexity science broadens conceptualizations of leadership from perspectives that are heavily invested in psychology and social psychology (e.g., human relations models) to include processes for managing dynamic systems and interconnectivity. We develop a definition of organizational complexity and apply it to leadership science, discuss strategies for enabling complexity and effectiveness, and delve into the relationship between complexity theory and other currently important leadership theories. The paper concludes with a discussion of possible implications for research strategies in the social sciences

Learning and Reflection in the Midst of Persistent Challenges on Practicing School Leaders’ Time

Among the many scarce resources that principals must conserve and use wisely, time may present one of the more persistent challenges to their leadership practices. A simultaneous and equally challenging practice for school leaders is engaging in systematic reflection that serves to mitigate time constraints and emotional upheavals of the job. Reflection, and resistance to it, emerged as a theme during a yearlong-program that emerged from a school-university partnership, focused on the development of district-level coaches to support experienced principals in becoming more reflective leaders for continuous school improvement. The program uncovered principals’ resistance to the pauses in their practices that reflection requires. These principals and coaches also reported emotional reactions to persisting mandates on school accountability. This paper offers some insights into how reflection may balance the ongoing emotional dynamics and time constraints of schooling, and the degree to which the mentoring program supported principal protégés in this effort

Continuous Humanoid Locomotion over Uneven Terrain using Stereo Fusion

Abstract — For humanoid robots to fulfill their mobility po-tential 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 continuously walk over rough and uneven surfaces without stopping. The perception system continuously integrates stereo imagery to build a consistent 3D model of the terrain which is then used by our footstep planner which reasons about obstacle avoidance, kinematic reachability and foot rotation through mixed-integer quadratic optimization to plan the required step positions. We illustrate that our stereo imagery fusion approach can measure the walking terrain with sufficient accuracy that it matches the quality of terrain estimates from LIDAR. To our knowledge this is the first such demonstration of the use of computer vision to carry out general purpose terrain estimation on a locomoting robot — and additionally to do so in continuous motion. A particular integration challenge was ensuring that these two computationally intensive systems oper-ate with minimal latency (below 1 second) to allow re-planning while walking. The results of extensive experimentation and quantitative analysis are also presented. Our results indicate that a laser range sensor is not necessary to achieve locomotion in these challenging situations. I

Optimization-based locomotion planning, estimation, and control design for the atlas humanoid robot

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 ranging from footstep placement to whole-body planning and control. We also present a state estimator formulation that, when combined with our walking controller, permits highly precise execution of extended walking plans over non-flat terrain. We describe our complete system integration and experiments carried out on Atlas, a full-size hydraulic humanoid robot built by Boston Dynamics, Inc.United States. Air Force Office of Scientific Research (FA8750-12-1-0321)United States. Office of Naval Research (N00014-12-1-0071)United States. Office of Naval Research (N00014-10-1-0951)National Science Foundation (U.S.) (IIS-0746194)National Science Foundation (U.S.) (IIS-1161909

An Architecture for Online Affordance-based Perception and Whole-body Planning

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, field-realistic communications link. We describe the design considerations, architecture, implementation and performance of the software that Team MIT developed to command and control an Atlas humanoid robot. Our design emphasized human interaction with an efficient motion planner, where operators expressed desired robot actions in terms of affordances fit using perception and manipulated in a custom user interface. We highlight several important lessons we learned while developing our system on a highly compressed schedule

SN 2000cx and SN 2013bh: extremely rare, nearly twin Type Ia supernovae

The Type Ia supernova (SN Ia) SN 2000cx was one of the most peculiar transients ever discovered, with a rise to maximum brightness typical of a SN Ia, but a slower decline and a higher photospheric temperature. 13 yr later SN 2013bh (also known as iPTF13abc), a near identical twin, was discovered and we obtained optical and near-infrared photometry and low-resolution optical spectroscopy from discovery until about 1 month past r-band maximum brightness. The spectra of both objects show iron-group elements [Co II, Ni II, Fe  II, Fe  III and high-velocity features (HVFs) of Ti  II], intermediate-mass elements (Si II, Si III and S  II) and separate normal velocity features (∼12 000 km s^(−1)) and HVFs (∼24 000 km s^(−1)) of Ca II. Persistent absorption from Fe III and Si III, along with the colour evolution, implies high blackbody temperatures for SNe 2013bh and 2000cx (∼12 000 K). Both objects lack narrow Na I D absorption and exploded in the outskirts of their hosts, indicating that the SN environments were relatively free of interstellar or circumstellar material and may imply that the progenitors came from a relatively old and low-metallicity stellar population. Models of SN 2000cx, seemingly applicable to SN 2013bh, imply the production of up to ∼1 M_⊙ of ^(56)Ni and (4.3–5.5) × 10^(−3) M_⊙ of fast-moving Ca ejecta