Spherical robots are a different type of mobility platform. A spherical robot is self-contained within its shell rather than relying on a chassis with wheels to navigate. In this shell, it is completely shielded from dust and the environment. This benefit of geometric simplicity has led to the spherical robot becoming an advantageous option for all-terrain exploration and surveying. This paper focuses on a novel iteration of such a robot with a pressurized pneumatic shell design. A soft robot of this type brings benefits of a passive, compliant contact surface that can affect its performance. However, the added softness of its shell adds new unmodeled dynamics into the system that impair commonly used control schemes. This paper outlines the design and manufacture of a soft, inflatable, spherical shell designed for a robot driven by an internal 2-DOF pendulum. In addition, it presents models for controlling the pendulum and understanding the shell dynamics. The paper concludes with experimental validations of these models and field tests of the system on slopes, gravel, rough grass, and on water.

Exploration robots are typically equipped with either wheels or legs for mobility. However, these conventional designs inherently possess certain limitations, such as restricted ability to navigate through steep slopes, soft soil or muddy watery terrain. Despite the advancements in robotics technoloy, these challenges persist in both terrestrial and extraterrestrial environments. To overcome these obstacles, we have proposed a novel solution in the form of a spherical robot with a soft shell. This paper provides an overview of the construction of this spherical robot and the design of its soft shell for adapting to varying terrain. Furthermore, we analyze and characterize its performance across various terrain types as the shell pressure is changed. By employing this approach, the paper establishes the suitability and efficiency of the spherical robot in traversing different terrain by adapting the shell pressure.

NASA and General Motors have developed the second generation Robonaut, Robonaut 2 or R2, and it is scheduled to arrive on the International Space Station in early 2011 and undergo initial testing by mid-year. This state of the art, dexterous, anthropomorphic robotic torso has significant technical improvements over its predecessor making it a far more valuable tool for astronauts. Upgrades include: increased force sensing, greater range of motion, higher bandwidth, and improved dexterity. R2's integrated mechatronic design results in a more compact and robust distributed control system with a fraction of the wiring of the original Robonaut. Modularity is prevalent throughout the hardware and software along with innovative and layered approaches for sensing and control. The most important aspects of the Robonaut philosophy are clearly present in this latest model's ability to allow comfortable human interaction and in its design to perform significant work using the same hardware and interfaces used by people. The following describes the mechanisms, integrated electronics, control strategies, and user interface that make R2 a promising addition to the Space Station and other environments where humanoid robots can assist people.

The Peer-To-Peer Human-Robot Interaction (P2P-HRI) project is developing techniques to improve task coordination and collaboration between human and robot partners. Our work is motivated by the need to develop effective human-robot teams for space mission operations. A central element of our approach is creating dialogue and interaction tools that enable humans and robots to flexibly support one another. In order to understand how this approach can influence task performance, we recently conducted a series of tests simulating a lunar construction task with a human-robot team. In this paper, we describe the tests performed, discuss our initial results, and analyze the effect of intervention on task performance.

This paper reports that the superposition of a small set of behaviors, learned via teleoperation, can lead to robust completion of an articulated reach-and-grasp task. The results support the hypothesis that a robot can learn to interact purposefully with its environment through a developmental acquisition of sensory-motor coordination. Teleoperation can bootstrap the process by enabling the robot to observe its own sensory responses to actions that lead to specific outcomes within an environment. It is shown that a reach-and-grasp task, learned by an articulated robot through a small number of teleoperated trials, can be performed autonomously with success in the face of significant variations in the environment and perturbations of the goal. In particular, teleoperation of the robot to reach and grasp an object at nine different locations in its workspace enabled robust autonomous performance of the task anywhere within the workspace. Superpositioning was performed using the Verbs and Adverbs algorithm that was developed originally for the graphical animation of articulated characters. The work was performed on Robonaut, the NASA space-capable humanoid at Johnson Space Center, Houston, TX.

A mobile version of the NASA/DARPA Robonaut humanoid recently completed initial autonomy trials working directly with humans in cluttered environments. This compact robot combines the upper body of the Robonaut system with a Segway ™ Robotic Mobility Platform yielding a dexterous, maneuverable humanoid ideal for interacting with human co-workers in a range of environments. This system uses stereovision to locate human teammates and tools and a navigation system that uses laser range and vision data to follow humans while avoiding obstacles. Tactile sensors provide information to grasping algorithms for efficient tool exchanges. The autonomous architecture utilizes these pre-programmed skills to form complex behaviors. The initial behavior demonstrates a robust capability to assist a human by acquiring a tool from a remotely located individual and then following the human in a cluttered environment with the tool for future use.

Engineers at the Johnson Space Center recently combined the upper body of the National Aeronautics and Space Administration (NASA) / Defense Advanced Research Projects Agency (DARPA) Robonaut system with a Robotic Mobility Platform (RMP) to make an extremely mobile humanoid robot designed to interact with human teammates. Virtual Reality gear that immerses a human operator into Robonaut's working environment provides the primary control pathway for remote operations. Human/robot interface challenges are addressed in the control system for teleoperators, console operators and humans working directly with the Robonaut. Multiple control modes are available for controlling the five fingered dexterous robot hands and operator selectable depending on the type of grasp required. A relative positioning system is used to maximize operator comfort during arm and head motions. Foot pedals control the mobility base. Initial tasks that include working with human rated tools, navigating hallways and cutting wires are presented and show the effectiveness of telepresence control for this class of robot.

The Johnson Space Center has developed a new mobile manipulation system with the combination of a Robonaut upper body mounted onto a Segway mobile base. The objective is to study a fluid and coordinated control of dexterous limbs on a mobile robot. The system has been demonstrated interacting with people, tools, and urban interfaces built for humans. Human interactions have included manually exchanging objects with humans, following people, and tracking people with hand held objects such as flashlights. Like other configurations of the Robonaut family, the upper body provides dexterity for using tools such as wire cutters, shovels, space flight gear, and handling flexible tethers and fabrics. The Segway base is a custom version called the Robotic Mobility Platform (RMP) built for DARPA, and provided to NASA for this collaborative effort. The RMP's active balance gives Robonaut a relatively small footprint for its height, allowing it to pass through doors and elevators built for humans, and use wheelchair accessible ramps and lifts. Lessons learned from this development are presented to improve the design of future mobile manipulation systems, and the Segway base provides mobility to Robonaut for Earth based testing.

Tactile data from rugged gloves are providing the foundation for developing autonomous grasping skills for the NASA/DARPA Robonaut, a dexterous humanoid robot. These custom gloves compliment the human like dexterity available in the Robonaut hands. Multiple versions of the gloves are discussed, showing a progression in using advanced materials and construction techniques to enhance sensitivity and overall sensor coverage. The force data provided by the gloves can be used to improve dexterous, tool and power grasping primitives. Experiments with the latest gloves focus on the use of tools, specifically a power drill used to approximate an astronaut's torque tool.

NASA's Human Space Flight program depends heavily on spacewalks performed by human astronauts. These Extra-Vehicular Activities (EVAs) are risky, expensive and complex. In collaboration with the Defense Advanced Research Projects Agency (DARPA), NASA is developing a robotic astronaut's assistant called Robonaut that can boost EVA productivity and help conserve human EVA hours. Robonaut is an anthropomorphic robot equipped with human-like dexterous manipulation and zero-g locomotion capabilities. In order to move about in a zero-g environment, a robot must be able to climb autonomously, using gaits that smoothly manage its momentum and that minimize contact forces while providing for safety in the event of an emergency requiring the system to stop. All three of these objectives are now being explored at NASA's Johnson Space Center with computer analysis and visualization tools as well as hardware tests involving the Robonaut system and a set of facilities and mockups that emulate the zero-g condition.

The NASA/DARPA Robonaut system is evolving from a purely teleoperator controlled anthropomorphic robot towards a humanoid system with multiple control pathways. Robonaut is a human scale robot designed to approach the dexterity of a space suited astronaut. Under teleoperator control, Robonaut has been able to perform many high payoff tasks indicating that it could significantly reduce the maintenance workload for human's working in space. Throughout its development, Robonaut has been augmented to include new sensors and software resulting in increased skills that allow for more shared control with the teleoperator, and ever increasing levels of autonomy. These skills range from simple compliance control, and short term memory, to, most recently, reflexive grasping and haptic object identification using a custom tactile glove, and real-time visual object tracking.

An automated tether system has been developed for the purpose of improving the efficiency of micro-gravity activities of fully suited astronauts. System features include gripping of multiple anchor types, remote release of the tether from an anchor, and controlled retraction of the tether. Two main mechanisms make up the system. First, a remotely releasable, self-locking robotic gripper with opposing jaws that grasps a variety of anchors such as handrails, tether loops, and guide wires. Second, an automated tether retractor that is capable of active or passive operation. Passive retractor operation saves power by emulating existing safety tether systems and active operation expedites tether retraction and allows towing.

The described mathematical formulations answer the questions "how strong is enough?", "strong in which direction?", and "where is the weakest link?" that robot designers face in the early stages of matching tasks with robotic mechanisms. This work produces 3D visualizations of robot strengths and weaknesses across their dexterous workspaces, aiding interactive manipulator joint and kinematic design. Strength is defined here as the maximum force or moment that the robot can exert on the environment at its point of resolution. This strength is a 6/spl times/1 vector for spatial mechanisms, comprising forces and moments resolved in a global frame. The three factors studied in this work are the design of the manipulator's drive trains, the chain's kinematic parameters, and the articulation of kinematic redundancies as self motion. The mathematical formulation is implemented as a minimum of a set of serial strengths, within which can exist parallel sets as appropriate for the mechanism's kinematics. The strength model is first developed for serial chains, broadened to the statically indeterminant cases of parallel chains, and then applied to a bifurcated system of chains in development at NASA. This work's primary objective is to bring to bear in robot design the mathematical principles usually reserved for robot modeling and control. After a robot has been built, it is often too late to fix a mechanism's many weaknesses. It is our belief that the Jacobian has as much to teach robot designers as it has taught students of dynamics and control theory.

Long duration manned missions to explore new environments require habitats with automated bioregenerative life support systems, since resupply from Earth is not feasible. Bioplex, the ground facility proposed by NASA Johnson Space Center for bioregenerative life support research, consists of cylindrical modules including biomass chambers that provide food and oxygen to support crew survival. Manual duties involved in processing and maintaining crops consume more calories that the crops can reasonably produce. Decreasing risk in the hazardous environment of distant closed systems, automation of crop tasks saves time and energy, reduces crew exposure to mold and exposed harvesting machinery, and improves efficiency. Automation needs are many in Bioplex but heavy hauling and lifting consume a substantial amount of calories, since the corridors in the chamber are narrow and cramped. Various configurations of a tray handling system, Traybot, were explored, resulting in an overhead two-rail system with a vertically driven basket. Modes of operation for harvest cycles determined the requirements for the chassis, basket, power, actuator and control components. In a hazardous environment, working along side humans demanded flexibility in design and control of Traybot. The Bioplex study found that Traybot's role is crucial to survival in space habitats.

NASA's Johnson Space Center has developed a general geometric model of a manipulator joint that allows for the interactive design and analysis of robot prototypes. The interactive design software analyzes joint geometries for various performance issues, and has been connected to a Stereolithography Apparatus (SLA) for the rapid production of full scale mechanism models. The software, called Module Maker, uses variational geometry to connect the joint model's 36 independent, geometric variables with over 100 dependent values that define the solids of a general 2 degree of freedom joint. A user can interactively "stretch" and edit the joint's structure, with a 3D rendering that updates in real time, while displaying numeric values for review. Analysis routines developed to support the interactive design process include a general evaluation of the joint's new range of motion, weight, moments of inertia, centroids, heat transfer coefficients and a calculation of the joint's Denavit-Hartenberg (DH) parameters. The final step in the design cycle is to prototype the module elements using an SLA that make full scale, polyurethane components.

The models developed here apply to both robot domains, where extreme thermal or precision conditions require a fundamental understanding of robot thermodynamics and heat transfer mechanisms that deform manipulators. A transient, 3D finite difference model is presented for tracking heat generated by actuators, conducted through the manipulator, radiated to space and absorbed from solar flux. Unlike large space cranes, the closely positioned actuators in small fine arms require modeling of energy exchange between joints, and simulations show that this heat transfer is governed by bearing elements. The consequences of torque histories can be predicted using these models, which link dynamics to future thermal states, and their resulting structural expansions and contractions. Thermal models can be coupled with distributed sensing to anticipate deformations in robots under operation in space conditions, improving precision and reducing the need for repeated calibration.

A two degree of freedom robot joint module was designed and built for the space environment, and evaluated in a thermal vacuum chamber at NASA's Johnson Space Center. The hypothesis was that servo dynamics would change across the wide temperature range of space, and a series of chamber experiments showed thermal adaptation is required to maintain response and stability over the EVA range of 223-373 K. A key finding was that control parameters selected for optimum dynamic response at room temperature were found to be inappropriate across the thermal vacuum range. At cold temperatures (233 K) the nominal gains were found to produce a critically damped response with large steady state error. At warm temperatures, the response was underdamped with significant overshoot, and at hot temperatures (353 K) the system went unstable, using gains that were optimal at room temperature. At each of seven thermal vacuum states, gains were found to deliver the desired dynamic response, and those settings were recorded.