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This paper presents the development of a compact, modular rotary series elastic actuator (SEA) design that can be customized to meet the requirements of a wide range of applications. The concept incorporates flat brushless motors and planetary gearheads instead of expensive harmonic drives and a flat torsional spring design to create a lightweight, low-volume, easily reconfigurable, and relatively high-performance modular SEA for use in active impedance controlled devices. The key innovations include a Hall effect sensor for direct spring displacement measurements that mitigate the negative impact of backlash on SEA control performance. Both torque and impedance controllers are developed and evaluated using a 1-degree-of-freedom (DoF) prototype of the proposed actuator package. The results demonstrate the performance of a stable first-order impedance controller tested over a range of target impedances. Finally, the flexibility of the modular SEA is demonstrated by configuring it for use in five different actuator specifications designed for use in the uBot-7 mobile manipulator requiring spring stiffnesses from 3 N · m/deg to 11.25 N · m/deg and peak torque outputs from 12 N · m to 45 N · m.

Abstract-We present the UMass uBot concept for dexterous mobile manipulation. The uBot concept is built around Bernstein's definition of dexterity-"the ability to solve a motor problem correctly, quickly, rationally, and resourcefully" [1]. We contend that dexterity in robotic platforms cannot arise from control alone and can only be achieved when the entire design of the robot affords resourceful behavior. uBot-6 is the latest robot in the uBot series whose design affords several postural configurations and mobility modes. We discuss these dexterous mobility options in detail and demonstrate the strength of dexterous mobility.

As part of a feasibility study, this paper shows the NASA Valkyrie humanoid robot performing an endto-end improvised explosive device (IED) response task. To demonstrate and evaluate robot capabilities, sub-tasks highlight different locomotion, manipulation, and perception requirements: traversing uneven terrain, passing through a narrow passageway, opening a car door, retrieving a suspected IED, and securing the IED in a total containment vessel (TCV). For each sub-task, a description of the technical approach and the hidden challenges that were overcome during development are presented. The discussion of results, which explicitly includes existing limitations, is aimed at motivating continued research and development to enable practical deployment of humanoid robots for IED response. For instance, the data shows that operator pauses contribute to 50% of the total completion time, which implies that further work is needed on user interfaces for increasing task completion efficiency. * The authors are with the 1 NASA Johnson Space Center, 2 TRACLabs, the 3 Institute for Human Machine and Cognition (IHMC), 4 Jacobs Technology, 5 METECS, 6 CACI, and 7 The University of Texas at Austin.

Symbolic planning methods have proved to be challenging in robotics due to partial observability and noise as well as unavoidable exceptions to rules that symbol semantics depend on. Often the symbols that a robot considers to support for planning are brittle, making them unsuited for even relatively short term use. Maturing probabilistic methods in robotics, however, are providing a sound basis for symbol grounding that supports using probabilistic distributions over symbolic entities as the basis for planning. In this paper, we describe a belief-space planner that stabilizes the semantics of feedback from the environment by actively interacting with a scene. When distributions over higher-level abstractions stabilize, powerful symbolic planning techniques can provide reliable guidance for problem solving. We present such an approach in a hybrid planning scheme that actively controls uncertainty and yields robust state estimation with bounds on uncertainty that can make effective use of powerful symbolic planning techniques. We illustrate the idea in a hybrid planner for autonomous construction tasks with a real robot system.