This paper describes a novel foot for biped robots designed to provide a reliable and low-cost solution for sensing the Center of Pressure (CoP) on flat and uneven surfaces. The foot uses a new method for detecting contact forces based on measuring the deflection of three flexural toes using Hall-effect magnetic field sensors. We experimentally compare five mathematical models for calculating the CoP coordinates from the sensor data. Results confirm that with the proposed method it is possible to obtain the same level of accuracy and reliability as with standard force sensing resistors, but without some the drawbacks of that approach.

We present a new bio-inspired system for automatically finding foot-scale curved surface patches in rough rocky terrain. These patches are intended to provide a reasonable set of choices for higher-level footfall selection algorithms, and are pre-filtered for several attributes - including location, curvature, and normal - that we observed humans to prefer. Input is from a 640 × 480 depth camera augmented with a 9-DoF inertial measurement unit to sense the direction of gravity. The system is capable of finding approximately 700 patches/second on commodity hardware, though the intention is not to find as many patches as possible but to reasonably sample upcoming terrain with quality patches. Sixty recordings of human subjects traversing rocky trails were analyzed to give a baseline for target patch properties. While the presented system is not designed to select a single foothold, it does find a set of patches for possible footholds which are statistically similar to the patches humans select.

Traditional segmentation algorithms for range images create partitions of connected and non-overlapping-but potentially irregularly shaped-regions corresponding to world surfaces. This paper presents an alternative paradigm based on regularly shaped curved patches (paraboloids) that model local contact regions potentially compatible with e.g. a robot's toe, heel, or fingertip. These patches randomly sample the environment surface but are not required to strictly partition it. They are fit to neighborhoods of the range data and then validated for fit quality and fidelity to the actual data-extrapolations (like hole-filling) which are not directly supported by data are avoided. Two different neighborhood formation methods based on k-d tree and triangle mesh data structures are compared, and results are presented for 10 datasets taken in natural rocky terrain.

Newcombe and Izadi et al’s KinectFusion [5] is an impressive new algorithm for real-time dense 3D mapping using the Kinect. It is geared towards games and augmented reality, but could also be of great use for robot perception. However, the algorithm is currently limited to a relatively small volume fixed in the world at start up (typically a ∼ 3m cube). This limits applications for perception. Here we report moving volume KinectFusion with additional algorithms that allow the camera to roam freely. We are interested in perception in rough terrain, but the system would also be useful in other applications including free-roaming games and awareness aids for hazardous environments or the visually impaired. Our approach allows the algorithm to handle a volume that moves arbitrarily on-line (Figure 1).

We introduce a set of 10 bounded curved-surface patch types suitable for modeling local contact regions both in the environment and on a robot. We present minimal geometric parameterizations using the exponential map for spatial pose both in the usual 6DoF case and also for patches with revolute symmetry that have only 5DoF. We then give an algorithm to fit any patch type to point samples of a surface, with quantified uncertainty both in the input points (including nonuniform variance, common in data from range sensors) and in the output patch. Finally, we outline how such patches can be composed into a spatial patch map of the available contact surfaces both on and around a robot.

This paper explores the space of active modular trusses, ranging from a passive truss with one independent active climbing module to fully self-reconfiguring dynamically controllable trusses comprised of active modules and passive struts. We describe a hardware design for truss climbing and present hierarchical algorithms for controlling hyper-redundant modular trusses

The Science Activity Planner (SAP) is the primary science operations tool for the Mars Exploration Rover mission and NASA’s Software of the Year for 2004. SAP utilizes a variety of visualization and planning capabilities to enable the mission operations team to direct the activities of the Spirit and Opportunity rovers. This paper outlines some of the challenging requirements that drove the design of SAP and discusses lessons learned from the development and use of SAP in mission operations.

We present an account of the scientific visualization techniques that were used to support science planning for NASA's 2003 Mars Exploration Rover Mission. The great sophistication of the rover's Athena Science Payload required a wide variety of visualization modalities to make the large amounts of scientific data accessible and readily understood by the science planners under the tight time constraints of the tactical planning schedule. A number of techniques were also newly developed to support science operations, including on-the-fly mosaic stitching and rendering, image cube visualization, and data fusion. Many other well-established visualization techniques were applied to science operations also, such as anaglyph stereo, high performance 3D visualization, and optimized I/O and memory management techniques for the loading, processing, and visualization of very large data sets. We discuss each of these topics and demonstrate their application in the MER mission with examples.

We describe VIsolate (Voronoi Isolate), a system which performs geometric computations associated with toolpath planning for mechanical etch (also called isolation routing) of printed-circuit boards, including the computation of a novel Voronoi-based toolpath with some advantages over the current industry practice. We highlight how we use the 3D Graphics Processing Unit (GPU) to implement simple, intuitive algorithms in VIsolate, including polygon overlap detection, 2D offset, and constrained generalized Voronoi diagram computation, building on a method from [1]. Thus, this work also illustrates how we can employ the GPU as a rudimentary ‘ mind’s eye’ for the machine, allowing us to rapidly implement visually-intuitive geometric algorithms.

We discuss a physical implementation of the crystalline robot system. Crystalline robots consist of modules that can aggregate together to form distributed robot systems. Crystalline modules are actuated by expanding and contracting each unit. This actuation mechanism permits automated shape metamorphosis. We describe the crystalline module concept and a physical implementation of a robot system with ten units. We describe experiments with this robot.

We discuss a basis for creating self-reconfiguring robots and instantiate it for crystal modules. Crystalline robots consist of modules that can aggregate together to form distributed robot systems. Crystalline modules are actuated by expanding and contracting each unit. This actuation mechanism permits automated shape metamorphosis. We describe the crystalline module concept and its physical implementation. We prove that crystalline robots are general self-reconfiguring robots.

We discuss a robotic system composed of crystalline modules. Crystalline modules can aggregate together to form distributed robot systems. Crystalline modules can move relative to each other by expanding and contracting. This actuation mechanism permits automated shape metamorphosis. We describe the crystalline module concept and show the basic motions that enable a crystalline robot system to self-reconfigure. We present an algorithm for general self-reconfiguration and describe simulation experiments.

We discuss a robotic module called a molecule. Molecules can be the basis for building self-reconfiguring robots. They support multiple modalities of locomotion and manipulation. We describe the design, functionality, and control of the molecule. We show how a set of molecules can aggregate as active three-dimensional structures that can move and change shape. Finally, we discuss our molecule experiments.