Sanjay S. Joshi

A systems theory approach to the feedback stabilization of infinitesimal and finite-amplitude disturbances in plane Poiseuille flow

A systems theory framework is presented for the linear stabilization of two-dimensional laminar plane Poiseuille flow. The governing linearized Navier{Stokes equations are converted to control-theoretic models using a numerical discretization scheme. Fluid system poles, which are closely related to Orr{Sommerfeld eigenvalues, and fluid system zeros are computed using the control-theoretic models. It is shown that the location of system zeros, in addition to the well-studied system eigenvalues, are important in linear stability control. The location of system zeros determines the eect of feedback control on both stable and unstable eigenvalues. In addition, system zeros can be used to determine sensor locations that lead to simple feedback control schemes. Feedback controllers are designed that make a new fluid{actuator{sensor{ controller system linearly stable. Feedback control is shown to be robust to a wide range of Reynolds numbers. The systems theory concepts of modal controllability and observability are used to show that feedback control can lead to short periods of highamplitude transients that are unseen at the output. These transients may invalidate the linear model, stimulate nonlinear eects, and/or form a path of ‘bypass’ transition in a controlled system. Numerical simulations are presented to validate the stabilization of both single-wavenumber and multiple-wavenumber instabilities. Finally, it is shown that a controller designed upon linear theory also has a strong stabilizing eect on two-dimensional nite-amplitude disturbances. As a result, secondary instabilities due to innitesimal three-dimensional disturbances in the presence of a nite-amplitude two-dimensional disturbance cease to exist.

Ground squirrels use an infrared signal to deter rattlesnake predation

The evolution of communicative signals involves a major hurdle; signals need to effectively stimulate the sensory systems of their targets. Therefore, sensory specializations of target animals are important sources of selection on signal structure. Here we report the discovery of an animal signal that uses a previously unknown communicative modality, infrared radiation or “radiant heat,” which capitalizes on the infrared sensory capabilities of the signals target. California ground squirrels (Spermophilus beecheyi) add an infrared component to their snake-directed tail-flagging signals when confronting infrared-sensitive rattlesnakes (Crotalus oreganus), but tail flag without augmenting infrared emission when confronting infrared-insensitive gopher snakes (Pituophis melanoleucus). Experimental playbacks with a biorobotic squirrel model reveal this signals communicative function. When the infrared component was added to the tail flagging display of the robotic models, rattlesnakes exhibited a greater shift from predatory to defensive behavior than during control trials in which tail flagging included no infrared component. These findings provide exceptionally strong support for the hypothesis that the sensory systems of signal targets should, in general, channel the evolution of signal structure. Furthermore, the discovery of previously undescribed signaling modalities such as infrared radiation should encourage us to overcome our own human-centered sensory biases and more fully examine the form and diversity of signals in the repertoires of many animal species.

Long-Term Training with a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients

Brain-machine interfaces (BMIs) provide a new assistive strategy aimed at restoring mobility in severely paralyzed patients. Yet, no study in animals or in human subjects has indicated that long-term BMI training could induce any type of clinical recovery. Eight chronic (3–13 years) spinal cord injury (SCI) paraplegics were subjected to long-term training (12 months) with a multi-stage BMI-based gait neurorehabilitation paradigm aimed at restoring locomotion. This paradigm combined intense immersive virtual reality training, enriched visual-tactile feedback, and walking with two EEG-controlled robotic actuators, including a custom-designed lower limb exoskeleton capable of delivering tactile feedback to subjects. Following 12 months of training with this paradigm, all eight patients experienced neurological improvements in somatic sensation (pain localization, fine/crude touch, and proprioceptive sensing) in multiple dermatomes. Patients also regained voluntary motor control in key muscles below the SCI level, as measured by EMGs, resulting in marked improvement in their walking index. As a result, 50% of these patients were upgraded to an incomplete paraplegia classification. Neurological recovery was paralleled by the reemergence of lower limb motor imagery at cortical level. We hypothesize that this unprecedented neurological recovery results from both cortical and spinal cord plasticity triggered by long-term BMI usage.

2005 Special Issue: The control of a parallel hybrid-electric propulsion system for a small unmanned aerial vehicle using a CMAC neural network

A Simulink model, a propulsion energy optimization algorithm, and a CMAC controller were developed for a small parallel hybrid-electric unmanned aerial vehicle (UAV). The hybrid-electric UAV is intended for military, homeland security, and disaster-monitoring missions involving intelligence, surveillance, and reconnaissance (ISR). The Simulink model is a forward-facing simulation program used to test different control strategies. The flexible energy optimization algorithm for the propulsion system allows relative importance to be assigned between the use of gasoline, electricity, and recharging. A cerebellar model arithmetic computer (CMAC) neural network approximates the energy optimization results and is used to control the parallel hybrid-electric propulsion system. The hybrid-electric UAV with the CMAC controller uses 67.3% less energy than a two-stroke gasoline-powered UAV during a 1-h ISR mission and 37.8% less energy during a longer 3-h ISR mission.

Brain–Muscle–Computer Interface: Mobile-Phone Prototype Development and Testing

We report prototype development and testing of a new mobile-phone-based brain-muscle-computer interface for severely paralyzed persons, based on previous results from our group showing that humans may actively create specified power levels in two separate frequency bands of a single surface electromyography (sEMG) signal. EMG activity on the surface of a single face muscle site (auricularis superior) is recorded with a standard electrode. This analog electrical signal is imported into an Android-based mobile phone and digitized via an internal A/D converter. The digital signal is split, and then simultaneously filtered with two band-pass filters to extract total power within two separate frequency bands. The user-modulated power in each frequency band serves as two separate control channels for machine control. After signal processing, the Android phone sends commands to external devices via a Bluetooth interface. Users are trained to use the device via visually based operant conditioning, with simple cursor-to-target activities on the phone screen. The mobile-phone prototype interface is formally evaluated on a single advanced Spinal Muscle Atrophy subject, who has successfully used the interface in his home in evaluation trials and for remote control of a television. Development of this new device will not only guide future interface design for community use, but will also serve as an information technology bridge for in situ data collection to quantify human sEMG manipulation abilities for a relevant population.

Robot work crews for planetary outposts: close cooperation and coordination of multiple mobile robots

We report on the development of cooperating multiple robots. This work builds form our earlier research on autonomous planetary rovers and robot arms. Here, we seek to closely coordinate the mobility and manipulation of multiple robots to perform site construction operations- as an example, the autonomous deployment of a planetary power station- a task viewed as essential to a sustained robotic presence and human habitation on Mars. There are numerous technical challenges; these include the mobile handling of extended objects, as well as cooperative transport/navigation of such objects over natural, unpredictable terrain. We describe an extensible system concept, related simulations, a hardware implementation, and preliminary experimental results. In support of this work we have developed an enabling hybrid control architecture wherein multi-robot mobility and sensor-based controls are derived as group compositions and coordination of more basic behaviors under a task-level multi-agent planner. We summarize this Control Architecture for Multi-robot Planetary Outposts (CAMPOUT), and its application to physical experiments where two rovers carry an extended payload over natural terrain.

Two-Dimensional Cursor-to-Target Control From Single Muscle Site sEMG Signals

In this study, human subjects achieve two-dimensional cursor-to-target control using the surface electromyogram (sEMG) from a single muscle site. The X-coordinate and the Y-coordinate of the computer cursor were simultaneously controlled by the active manipulation of power within two frequency bands of the sEMG power-spectrum. Success of the method depends on the sEMG frequency bandwidths and their midpoints. We acquired the sEMG signals at a single facial muscle site of four able-bodied subjects and trained them, by visual feedback, to control the position of the cursor. After training, all four subjects were able to simultaneously control the X and Y positions of the cursor to accurately and consistently hit three widely-separated targets on a computer screen. This technology has potential application in a wide variety of human-machine interfaces to assistive technologies.

Rat pups and random robots generate similar self-organized and intentional behavior

Biorobotic research continually demonstrates that behavior and cognition can be the emergent products of (1) embodied agents that are (2) dynamically embedded within an environment and (3) equipped with simple sensorimotor rules. Thigmotaxis is an orientation response to contact manifested in infant rats by wall following, corner burrowing, and group aggregation. Orientation responses have been long thought to be mediated only by sensory or central processes. Here we show that a random control architecture in a morphologically similar robot embedded in a scaled environment can reproduce thigmotaxic behaviors seen in infant rats. We conclude that (1) and (2) may play a larger role than previously thought in the generation of complex behaviors.

CAMPOUT: A control Architecture for multi-robot Planetary outposts

A manned Mars habitat will require a significant amount of infrastructure that can be deployed using robotic precursor missions. This infrastructure deployment will probably include the use of multiple, heterogeneous, mobile robotic platforms. Delays due to the long communication path to Mars limit the amount of teleoperation that is possible. A control architecture called CAMPOUT (Control Architecture for Multirobot Planetary Outposts) is currently under development at the Jet Propulsion Lab in Pasadena, CA. It is a three layer behavior-based system that incorporates the low level control routines currently used on the JPL SRR/FIDO/LEMUR rovers. The middle behavior layer uses either the BISMARC (Biologically Inspired System for Map- based Autonomous Rover Control) or MOBC (Multi-Objective Behavior Control) action selection mechanisms. CAMPOUT includes the necessary group behaviors and communication mechanisms for coordinated/cooperative control of heterogeneous robotic platforms. We report the results of some ongoing work at the jet Propulsion Lab in Pasadena, CA on the transport phase of a photovoltaic (PV) tent deployment mission.

A Biorobotic Investigation of Norway Rat Pups (Rattus norvegicus) in an Arena

Biorobotics research typically focuses on simulating specific aspects of animal biomechanics, sensory systems, and computational abilities. We have developed a novel methodology for integrating the study of biorobotics and animal behavior. We describe several metrics for characterizing and comparing rat pup and robot behavior without presupposing behavioral goal states. In the rat pup and robot experiments, we found that when 10-day-old Norway rats (Rattus Norvegicus) are placed in an arena, they typically follow walls to a single corner and stay there. However, our thigmotaxic robots followed walls but typically circumnavigated the entire arena, contacting all corners, and exhibiting asymmetric corner behavior. After observing the latter behavior in robots, we found that rat pups also exhibited asymmetric corner behavior. Thus, our robotic experiments, while not quantitatively matching pup behavior, led to the discovery of a previously unrecognized pattern of behavior in rat pups. This illustrates the value of models in leading to discovery of new patterns of behavior in the system modeled. Our results also show that simple thigmotaxic architectures alone may not explain pup behavior in an arena.