Carl A. Moore

Passive robots and haptic displays based on nonholonomic elements

Describes a new architecture for passive robots and haptic displays, which the authors call a programmable constraint machine (PCM). An n-DOF PCM can, under computer control, exhibit constraints (smooth, impenetrable virtual surfaces of dimensionality <n), or it can allow free n-DOF motion. At the heart of the PCM is a nonholonomic element, which is used as a continuously variable transmission (CVT). A rolling wheel, for instance, can be used as a CVT. A prototype 2-DOF cartesian PCM has been built, using a single rolling wheel. The authors sketch PCMs of higher dimensionality. A rolling wheel may be thought of as a translational CVT, coupling the x and y velocities of its center by a transmission ratio which is the tangent of its steering angle, Its utility in a cartesian PCM motivates interest in a rotational analog for revolute architectures. The authors develop a novel rotational CVT which couples two angular velocities by an adjustable ratio.

Cobot implementation of virtual paths and 3D virtual surfaces

Cobots are devices for human/robot interaction, in which axes of motion are coupled to one another by computer-controlled continuously variable transmissions rather than individually driven by servomotors. We have recently built a cobot with a three-dimensional workspace and a 3-revolute parallelogram-type mechanism. Here we present the control methods for the display of virtual surfaces and for free mode in which the cobot endpoint moves as if it were unconstrained. We provide experimental results on the performance of the free, virtual path, and virtual surface controllers.

Frequency response method for terrain classification in autonomous ground vehicles

Abstract Many autonomous ground vehicle (AGV) missions, such as those related to agricultural applications, search and rescue, or reconnaissance and surveillance, require the vehicle to operate in difficult outdoor terrains such as sand, mud, or snow. To ensure the safety and performance of AGVs on these terrains, a terrain-dependent driving and control system can be implemented. A key first step in implementing this system is autonomous terrain classification. It has recently been shown that the magnitude of the spatial frequency response of the terrain is an effective terrain signature. Furthermore, since the spatial frequency response is mapped by an AGV’s vibration transfer function to the frequency response of the vibration measurements, the magnitude of the latter frequency responses also serve as a terrain signature. Hence, this paper focuses on terrain classification using vibration measurements. Classification is performed using a probabilistic neural network, which can be implemented online at relatively high computational speeds. The algorithm is applied experimentally to both an ATRV-Jr and an eXperimental Unmanned Vehicle (XUV) at multiple speeds. The experimental results show the efficacy of the proposed approach.

Online Terrain Classification for Mobile Robots

Today’s autonomous vehicles operate in an increasingly general set of circumstances. In particular, unmanned ground vehicles (UGV’s) must be able to travel on whatever terrain the mission offers, including sand, mud, or even snow. These terrains can affect the performance and controllability of the vehicle. Like a human driver who feels his vehicle’s response to the terrain and takes appropriate steps to compensate, a UGV that can autonomously perceive its terrain can also make necessary changes to its control strategy. This article focuses on the development and application of a terrain detection algorithm based on terrain induced vehicle vibration. The dominant vibration frequencies are extracted and used by a probabilistic neural network to identify the terrain. Experimental results based on iRobot’s ATRV Jr (Fig. 1) demonstrate that the algorithm is able to identify with high accuracy multi-differentiated terrains broadly classified as sand, grass, asphalt, and gravel.Copyright

Cobot implementation of 3D virtual surfaces

Cobots are devices for human/robot interaction, in which axes of motion are coupled to one another by computer-controlled continuously variable transmissions rather than individually driven by servomotors. We have recently built a 3R parallelogram cobot. Here we present a control method for the display of virtual surfaces and for free-mode in which the cobot endpoint moves as if it were unconstrained. We show experimental results on the performance of the cobot in these modes.

Terrain classification for mobile robots traveling at various speeds: An eigenspace manifold approach

Unmanned ground vehicles (UGVs) commonly used in military applications must possess the capability to traverse various terrains that may largely affect the performance and controllability of the vehicle. A UGV that can autonomously perceive its terrain using navigational sensors can make necessary changes to its control strategy. The research presented uses the output of the induced vehicles vibration measured by navigational sensors to classify the underlying terrain at multiple speeds. The classification algorithm incorporates Principal Component Analysis (PCA) for feature extraction and dimension reduction. The PCA transformation coefficients are then used to develop a manifold curve that uses these known coefficients to interpolate unknown coefficients of the terrains as the robots speed changes. Experimental data is collected using two distinctly different unmanned ground vehicle platforms. Results demonstrate the performance of the method for classifying multi-differentiated terrains broadly classified as grass, asphalt, mud, and gravel.

Kinematic Creep in a Continuously Variable Transmission: Traction Drive Mechanics for Cobots

Two continuously variable transmissions are examined, one that relates a pair of linear speeds and another that relates a pair of angular speeds. These devices are elemental in the design of cobots, a new class of robot that creates virtual guiding surfaces to aid a human operator in assembly tasks. Both of these transmissions are traction drive mechanisms that rely on the support of either lateral or longitudinal forces across rolling contacts with spin. When a rolling contact between elastic bodies or even between rigid bodies in spin is called upon to transmit a tractive force, kinematic creep develops, expressing a departure from the intended rolling constraint. Creep in turn gives rise to nonideal properties in a cobot’s virtual guiding surfaces. This paper develops simple models of the two transmissions by expressing the relative velocity field in the contact patch between rolling bodies in terms of creep and spin. Coulomb friction laws are applied in a quasi-static analysis to produce complete force-motion models. These models may be used to evaluate a cobot’s ability to support forces against its virtual guiding surfaces. @DOI: 10.1115/1.1517560#

Calculation of wall shear stress in left coronary artery bifurcation for pulsatile flow using two-dimensional computational fluid dynamics.

The onset of coronary heart disease may be governed by distribution and magnitude of hemodynamic shear stress in the coronary arteries. This study numerically examines pulsatile blood flow through the left coronary artery system. A triphasic waveform is employed to simulate pulsating flow. Five non-Newtonian models, as well as the usual Newtonian model, are used to describe the viscous shear-thinning behavior of blood. It is concluded that when using computational fluid dynamics (CFD) to numerically investigate blood velocity profiles within small arteries, such the coronary artery system examined in this work, great care should be taken in choosing a blood viscosity model. It is suggested that the generalized power law model be the viscous shear thinning model of choice. When using CFD to investigate only patterns of wall shear stresses, the model selection is not as crucial and the simple Newtonian model will suffice but when the magnitude of WSS is of great importance, as in the case of the determining the development of coronary artery disease, the model selection is key

Fuzzy behavior navigation for an unmanned helicopter in unknown environments

Aerial missions that require unmanned aerial vehicles (UAVs) to fly autonomously in unknown and hostile environments are inevitable. These UAVs must be equipped with a fully autonomous navigation system. Many methods that have been proposed for navigation of autonomous systems either lack the necessary intelligence or are not responsive enough to cope with the flying speeds of UAVs. This paper presents a new method for autonomous navigation of UAVs using reactive fuzzy behaviors. It extends a 2D fuzzy behavior navigation system used in unmanned ground vehicles to a 3D navigation system suitable for UAVs. The research is based on a range finding sensor system by judicious use of a 2D range finder. A novel defuzzification method for 3D navigation systems is developed to generate the most desired flying orientation. Simulation results carried out using MATLABs Virtual Reality Toolbox show that the proposed system works very well to avoid static obstacles.

Off-road robot modeling with dextrous manipulation kinematics

We present a novel way of modeling wheeled vehicles on outdoor terrains. Adapting concepts from dextrous manipulation, we precisely model the way that three dimensional wheels roll over uneven ground. The techniques used are easily adaptable to other vehicle designs of arbitrary complexity. Our modeling method is used to validate a new concept for design of off-road vehicle wheel suspensions, called passive variable camber (PVC). Simulation results of a three-wheeled vehicle with PVC demonstrate that the vehicle can negotiate an extreme terrain without kinematic slip, thus improving vehicle efficiency and performance.