The discovery of ocean worlds such as Enceladus, Titan, and Europa motivates the development of versatile autonomous mobility systems to enable the next era of space exploration where there is large uncertainty in terrain specifications due to a lack of prior surface reconnaissance missions. To explore these environments, we propose Exobiology Extant Life Surveyor (EELS): the first large-scale (4 lm long with 400 Nm peak torque) snake robot. The large scale is achieved by using a screw-based active skin mechanism to decouple motion and shape control. Autonomous mobility for such a system remains an open problem due to its many Degrees of Freedom (DoFs), complex terrain interactions, and intermittent localization failures in GPS-denied perceptually degraded environments due to the presence of fog, dust, featureless terrains, etc. We propose NEO, an autonomy architecture that scales to large DoFs to generate a versatile set of gaits to achieve mobility in unknown extreme environments. We also discuss the resilience capabilities of NEO that achieves closed-loop tracking performance by leveraging exteroception when available but can also operate with proprioception only, leading to resiliency against localization failures via graceful degradation in performance rather than unsafe behaviors. A quantitative hardware evaluation of exteroceptive leader-follower gait is performed indoors on synthetic ice along with qualitative results of field deployment of the proprioceptive leader-follower and sidewinding gaits in extreme environments of icy and sandy terrains with mobility-stressing elements such as trenches, undulations, and steep slopes (up to 35 degrees). We present a set of lessons learned from field deployments with a summary of challenges and open research problems. Video: www.rohanthakker.in/eels-neo-autonomy.html

Opportunities to evoke emotional experiences and modulate cognitive processes hold great importance in studying relations between emotion, cognition and behaviour as well as building technologies for maintaining positive mental health. We present the concept of Metasomatic Interactions as a new way of generating and controlling previously untapped embodied emotions using illusory sensations tuned to the prior bodily experiences. We present Frisson, a metasomatic interface built to elicit the sensations underlying the embodied emotion of aesthetic chills (i.e., goosebumps, psychogenic shivers). We present a user study (N = 14) in which the device evokes the psychogenic experience of aesthetic chills by simulating traversing thermal sensations across the spine when the illusory sensations overlap with the prior impression of aesthetic chills. The results encourage further testing of metasomatic interfaces for inducing emotions from the body. Using theories of embodied cognition, experimental results and this device, we present a discussion on characteristics of metasomatic interfaces, which we hope will inspire new categories of emotional prostheses in HCI.

Where does human agency remain in the era of automation and intelligent machineries? Technological affordances create instant ways of accomplishing challenging tasks, where a lot of individual agency is mitigated. In this installation, we present an autonomous musical instrument that invites volunteers to eventually take a subordinate role to machines. Over time, the instrument gradually raises its level of autonomy, eventually overriding through musical patterns impractical to play by users. Juxtaposing machine uprising and an artifact that manifests human creativity, we question the relationship between technology and human on the continuum of symbiosis and adversary, through orders of algorithmic complexity and intensity in the act of music.

We present a small and lightweight wearable device that enhances virtual reality experiences and reduces cybersickness by means of galvanic vestibular stimulation (GVS). GVS is a specific way to elicit vestibular reflexes that has been used for over a century to study the function of the vestibular system. In addition to GVS, we support physiological sensing by connecting heart rate, electrodermal activity and other sensors to our wearable device using a plug and play mechanism. An accompanying Android app communicates with the device over Bluetooth (BLE) for transmitting the GVS stimulus to the user through electrodes attached behind the ears. Our system supports multiple categories of virtual reality applications with different types of virtual motion such as driving, navigating by flying, teleporting, or riding. We present a user study in which participants (N = 20) experienced significantly lower cybersickness when using our device and rated experiences with GVS-induced haptic feedback as significantly more immersive than a no-GVS baseline.

Virtual and augmented reality headsets are unique as they have access to our facial area: an area that presents an excellent opportunity for always-available input and insight into the user's state. Their position on the face makes it possible to capture bio-signals as well as facial expressions. This paper introduces the PhysioHMD, a software and hardware modular interface built for collecting affect and physiological data from users wearing a head-mounted display. The PhysioHMD platform is a flexible architecture enables researchers and developers to aggregate and interprets signals in real-time, and use those to develop novel, personalized interactions and evaluate virtual experiences. Offering an interface that is not only easy to extend but also is complemented by a suite of tools for testing and analysis. We hope that PhysioHMD can become a universal, publicly available testbed for VR and AR researchers.

This paper presents a model based approach to autonomous dexterous manipulation, developed as part of the DARPA Autonomous Robotic Manipulation (ARM) program. The developed autonomy system uses robot, object, and environment models to identify and localize objects, and well as plan and execute required manipulation tasks. Deliberate interaction with objects and the environment increases system knowledge about the combined robot and environmental state, enabling high precision tasks such as key insertion to be performed in a consistent framework. This approach has been demonstrated across a wide range of manipulation tasks, and in independent DARPA testing archived the most successfully completed tasks with the fastest average task execution of any evaluated team.

Spatial operators have been used to analyze the dynamics of robotic multibody systems and to develop novel computational dynamics algorithms for them. Mass matrix factorization, inversion, diagonalization, linearization are among the several techniques developed using operators. These techniques have been shown to apply broadly to systems ranging from serial, tree, to closed topology systems, as well as to systems with rigid and flexible links/joints. This paper uses concepts from graph theory to obtain a deeper understanding of the mathematical foundations of spatial operators. We show that spatial kernel operators are instances of block weighted adjacency matrices for the underlying multibody topology graphs, and that spatial propagation operators are 1-resolvents of these matrices. We explore at an abstract level the properties of such 1-resolvents in order to understand the precise requirements on and the range of applicability of spatial operators to the broad class of dynamics problems.

This paper describes spatial operators in robot dynamics, emphasizing their physical interpretation, while avoiding lengthy mathematical derivations. The spatial operators are rooted in the function space approach to the estimation theory developed in the decades that followed the introduction of the Kalman filter. In the mid 1980's, the authors recognized the analogy between Kalman filtering and robot dynamics, and began to use this approach on a wide range of multi-body systems of increasing complexity. This paper reviews the spatial operator approach to robot dynamics, and outlines current applications to the modeling, simulation and control of space robot dynamics and large molecular structures.

A diagonal equation for robot dynamics is developed by combining mass matrix factorization results with classical Lagrangian mechanics. Diagonalization implies that at each fixed time instant the equation at each joint is decoupled from all of the other joint equations. The equation involves two important variables: a vector of total joint rotational rates and a corresponding vector of working joint moments. The nonlinear Coriolis term depends on the joint angles and the rates. The total joint rates are related to the relative joint-angle rates by a linear spatial operator. The total rate at a given joint k reflects the total rotational velocity about the joint, and includes the combined effects from all the links between joint k and the base. Similarly, the working moments are related to the applied moments by the spatial operator . The working moment at a given joint is that part of the applied moment which does actual mechanical work. The diagonal equations are obtained by using the mass matrix factorization in the system Lagrangian.>

The freedom of choice in designating a base-body for free-flying manipulators gives these manipulators a base-invariance symmetry that is not encountered in fixed-base manipulators. This paper analyzes the relationship between this natural symmetry and the dynamical equations for free-flying manipulators. The base-invariance symmetry is used to develop a new formulation of the manipulator dynamics in which two independent O(N) recursions proceeding in opposite directions are summed together to obtain the complete free-flying manipulator dynamics. Computation of the operational space inertia for the links in the manipulator is also discussed.>

A diagonal equation /spl nu//spl dot/+C(/spl theta/, /spl nu/)=/spl epsiv/ for robot dynamics is developed by combining mass matrix factorization results with classical Lagrangian mechanics. The nonlinear Coriolis term C(/spl theta/, /spl nu/) depends on the joint angles /spl theta/ and the rates /spl nu/ and does no work. The total joint rates /spl nu/=m*(/spl theta/)/spl theta//spl dot/ are related to the relative joint-angle rates /spl theta//spl dot/ by a linear spatial operator m*(/spl theta/) mechanized by a base-to-tip spatially recursive algorithm.>

The dynamics and kinematics of manipulators that have fewer actuators than degrees of freedom are studied. These underactuated manipulators arise in a number of important applications such as free-flying space robots, hyperredundant manipulators, manipulators with structural flexibility, etc. In the analysis such underactuated manipulators are decomposed into component active and passive arms. This decomposition allows techniques previously developed for regular (fully actuated) manipulators to be applied to underactuated systems. Spatial operator identities are used to develop closed-form expressions for the generalized accelerations for the system. These expressions form the basis for a recursive O(N) dynamics algorithm. The structure of this algorithm is a hybrid of known forward and inverse dynamics algorithms for regular manipulators. Expressions and computational algorithms are also developed for the generalized and disturbance Jacobians for underactuated manipulators. The application of the results in the paper to space manipulators is also described.>

Techniques from the spatial operator algebra are used to obtain closed-form operator expressions for two types of linearized dynamics models: the linearized inverse and forward dynamics models. Spatially recursive algorithms of O(n) and O(n/sup 2/) complexity for the computation of the perturbation vector and coefficient matrices for the linearized inverse dynamics model (LIDM) are developed. Operator factorization and inversion identities are used to develop corresponding closed-form expressions for the linearized forward dynamics model (LFDM). Once again, these are used to develop algorithms of O(n) and O(n/sup 2/) complexity for the computation of the perturbation vector and the coefficient matrices. The algorithms for the LFDM do not require the explicit computation of the mass matrix nor its numerical inversion and are also of lower complexity than the conventional O(n/sup 3/) algorithms.>

The kinematics and dynamics of underactuated manipulators are discussed. It is shown that, due to the presence of passive hinges, the dynamics of the underactuated manipulators are considerably more complex than those of fully actuated manipulators. Spatial operator algebra techniques are used to develop expressions for the dynamical equations of motion, the mass matrix, the generalized Jacobian, and the Jacobian that describes the coupling between the motions of the active and passive hinges. An efficient and recursive inverse dynamics algorithm, the complexity of which depends only linearly on the number of degrees of freedom, is also described. The structure of this algorithm is a hybrid combination of well-known inverse and forward dynamics algorithms for fully actuated manipulators.>

The spatial operator algebra methodology is used to develop efficient spatially recursive algorithms for the dynamics of flexible link manipulators. The operator-based formulation closely parallels that for rigid link manipulators. The computational complexity of the forward dynamics algorithm is linear in the number of links and cubic in the number of modes.>

A spatial operator algebra approach to modeling and analysis of multibody robotic systems is discussed. It is shown that this modeling and analysis method can be used to develop O(n) recursive algorithms that compute the operational space mass matrix and the operational space coriolis/centrifugal and gravity terms of an n-link serial chain manipulator. It is also shown that, taken together, these algorithms enable an O(n) recursive implementation of operational space control.>

The spatial operator algebra developed by the authors for modeling control and trajectory design of manipulation is discussed, with emphasis on the analytical formulation of the operator algebra and its simple implementation in the Ada programming language. The elements of this algebra are linear operators whose domain and range spaces consist of forces, moments, velocities, and accelerations. The effect of these operators is equivalent to a spatial recursion along the span of the manipulator. Inversion of operators can be efficiently obtained using techniques of recursive filtering and smoothing. The operator algebra provides a high-level framework for describing the dynamic and kinematic behavior of a manipulator and control and trajectory design algorithms. The interpretation of expressions within the algebraic framework leads to enhanced conceptual and physical understanding of manipulator dynamics and kinematics. Furthermore, implementable recursive algorithms can be immediately derived from the abstract operator expressions by inspection. Thus, the transition from an abstract problem formulation and solution to the detailed mechanization of specific algorithm is greatly simplified.>

A general formulation of the optimal control model of the human operator is presented. This formulation dispenses with the assumption that the operator has an accurate internal model of the system dynamics and other parameters affecting his control behavior. It has applications to learning and transfer of training situations where the operator refines his behavior over a period of time. Validation of the model is via analysis of a flight control experiment using a discrete transfer of the training protocol.>