The birth of spinplasmonics
You might have heard of spintronics, a technology that uses the magnetic quantum properties of the spin of electrons, or plasmonics, another one which ‘involves the transfer of light electromagnetic energy into a tiny volume, thus creating intense electric fields.’ Now, researchers at the University of Alberta (U of A) have merged these two nascent research fields to create a new nanotechnology field called spinplasmonics. [Note: And when I say ‘new,’ it really is: Google returned only 25 pages containing the word spinplasmonics today.] According to the researchers, this new technology, which was already used to control the quantum state of an electron’s spin to switch a beam of terahertz light, could one day be the basis for ‘computers with extraordinary capacities.’
Modular Reactive Neurocontrol for Biologically Inspired Walking Machines
A neurocontroller is described which generates the basic locomotion and controls the sensor-driven behavior of a four-legged and a six-legged walking machine. The controller utilizes discrete-time neurodynamics, and is of modular structure. One module is for processing sensor signals, one is a neural oscillator network serving as a central pattern generator, and the third one is a so-called velocity regulating network. These modules are small and their structures and their functionalities are analyzable. In combination, they enable the machines to autonomously explore an unknown environment, to avoid obstacles, and to escape from corners or deadlock situations. The neurocontroller was developed and tested first using a physical simulation environment, and then it was successfully transferred to the physical walking machines. Locomotion is based on a gait where the diagonal legs are paired and move together, e.g. trot gait for the four-legged walking machine and tripod gait for the six-legged walking machine. The controller developed is universal in the sense that it can easily be adapted to different types of even-legged walking machines without changing the internal structure and its parameters.
ManyEars Microphone Array Processing Software
Microphones can make inexpensive sensors for mobile robots. If your robot doesn’t sense sound yet, this might be an interesting way to add that capability. ManyEars is Free Software licensed with the GNU GPL. -more-
Autonomous Helicopter Tracking and Localization Using a Self-surveying Camera Array
A Self-surveying Camera Array (SSCA) is a vision-based local-area positioning system consisting of multiple ground-deployed cameras that are capable of self-surveying their extrinsic parameters while tracking and localizing a moving target. This paper presents the self-surveying algorithm being used to track a target helicopter in each camera frame and to localize the helicopter in an array-fixed frame. Three cameras are deployed independently in an arbitrary arrangement that allows each camera to view the helicopter’s flight volume. The helicopter then flies an unplanned path that allows the cameras to calibrate the relative locations and orientations by utilizing a self-surveying algorithm that is extended from the well-known structure from motion algorithm and the bundle adjustment technique. This yields the cameras’extrinsic parameters enabling real-time helicopter positioning via triangulation. This paper also presents results from field trials, which verify the feasibility of the SSCA as a readily-deployable system applicable to helicopter tracking and localization. The results demonstrate that, compared to the differential GPS solution as true reference, the SSCA alone is capable of positioning the helicopter with meter-level accuracy. The SSCA has been integrated with onboard inertial sensors providing a reliable positioning system to enable successful autonomous hovering.
Transfer Time Complexity of Conflict-free Vehicle Routing with no Communications
The following motion coordination problem is studied: given n mobile vehicles and n source-destination pairs in the plane, what is the minimum time needed to transfer each vehicle from its source to its destination, avoiding conflicts with other vehicles? In the proposed model, vehicles do not explicitly communicate their intentions, and only have sensory information about the current position and velocity of their neighbors to ensure no conflicts. The environment is free of obstacles and a conflict occurs when the distance between any two vehicles is smaller than a velocity-dependent safety distance. The situation analyzed in which the vehicle size is such that at least a constant fraction of the n vehicles can be fitted inside the environment simultaneously. In the “best” case in which the source and destination points can be chosen ideally to maximize the transfer efficiency, it is shown that the transfer takes ([UNKNOWN][UNKNOWN]n) time to complete, where [UNKNOWN] is the average distance between the source and destination points. It is shown that there exist a “worst” case distribution of the source and destination points, for which the transfer of vehicles takes at least (n) time. The case is also analyzed in which source and destination points are generated randomly according to a uniform distribution, and an algorithm is presented providing a constructive upper bound on the time needed to transfer vehicles from sources to their corresponding destinations, proving that the transfer takes ([UNKNOWN]n) time, with high probability, thus recovering the best case performance.
Optimal Rough Terrain Trajectory Generation for Wheeled Mobile Robots
An algorithm is presented for wheeled mobile robot trajectory generation that achieves a high degree of generality and efficiency. The generality derives from numerical linearization and inversion of forward models of propulsion, suspension, and motion for any type of vehicle. Efficiency is achieved by using fast numerical optimization techniques and effective initial guesses for the vehicle controls parameters. This approach can accommodate such effects as rough terrain, vehicle dynamics, models of wheel-terrain interaction, and other effects of interest. It can accommodate boundary and internal constraints while optimizing an objective function that might, for example, involve such criteria as obstacle avoidance, cost, risk, time, or energy consumption in any combination. The algorithm is efficient enough to use in real time due to its use of nonlinear programming techniques that involve searching the space of parameterized vehicle controls. Applications of the presented methods are demonstrated for planetary rovers.
Tracking contaminated airline cabins
With the numbers of airline passengers always increasing, the regulation authorities are more concerned than ever by the possible contamination of air cabins by contagious viruses, such as SARS or H5N1. This is why Purdue University researchers have developed a system that can track a pathogen substance to an area the size of a single seat. The system uses sensors to locate passengers releasing hazardous materials. But more importantly, it uses a mathematical technique, called ‘inverse simulation,’ which analyzes ‘how a material disperses throughout the cabin and then runs the dispersion in reverse to find its origin.’ This system could one day alert the pilots in real time — and even be deployed in office buildings.
Adaptive Dynamic Walking of a Quadruped Robot on Natural Ground Based on Biological Concepts
The paper reports on a project to make a quadruped robot walk with medium forward speed on irregular terrain in an outdoor environment using a neural system model. The necessary conditions for stable dynamic walking on irregular terrain in general are proposed, and the neural system is designed by comparing biological concepts with those necessary conditions described in physical terms. A PD-controller is used at joints to construct a virtual spring—damper system as the visco-elasticity model of a muscle. The neural system model consists of a CPG (central pattern generator), responses and reflexes. A response directly and quickly modulates the CPG phase, and a reflex directly generates joint torque. The state of the virtual spring—damper system is switched, based on the CPG phase. In order to make a self-contained quadruped (called Tekken2) walk on natural ground, several new reflexes and responses are developed in addition to those developed in previous studies. A flexor reflex prevents a leg from stumbling on small bumps and pebbles. A sideways stepping reflex stabilizes rolling motion on a sideways inclined slope. A corrective stepping reflex/response prevents the robot from falling down in the case of loss of ground contact. A crossed flexor reflex helps a swinging leg keep enough clearance between the toe and the ground. The effectiveness of the proposed neural system model control and especially the newly developed reflexes and responses are validated by indoor and outdoor experiments using Tekken2. A CPG receives sensory feedback as a result of motions induced by reflexes, and changes the period of its own active phase. Since a CPG has the ability of mutual entrainment with pitching motion of legs and rolling motion of the body in addition, the consistency between motion of a leg temporally modified by a reflex and motions of the other legs is maintained autonomously. It is shown that CPGs can be the center of sensorimotor coordination, and that the neural system model simply defining the relationships between CPGs, sensory input, reflexes and mechanical system works very well even in complicated tasks such as adaptive dynamic walking on unstructured natural ground.
Manipulation of Convex Objects via Two-agent Point-contact Push
This paper explores a sensorless manipulation method for orienting and translating convex objects in the plane. The manipulation task is performed by a two-agent point-contact push. During the manipulation, each agent makes a point contact with the object, and both agents push together along a straight-line. One advantage of the two-agent point-contact push over the physical fence based push is that the two-agent point-contact push can manipulate non-polygonal parts, and reduce the position and orientation uncertainties simultaneously. First, two manipulation primitives are identified, equilibrium and non-equilibrium pushes, and the motion of the object characterized under these two pushing actions. Then, a controllability analysis is conducted for this class of manipulation using the theory of positive bases. After the analysis, the planning problem is studied in the framework of a switched system, and an analytical solution to the planning problem is developed. Finally, manipulation examples and experiments are provided to demonstrate the proposed manipulation method.
Robust Fault Detection of a Robotic Manipulator
In this paper, a new robust fault detection technique for robotic manipulators is developed. The new approach, called robust nonlinear analytic redundancy (RNLAR) technique, detects both sensor and actuator faults in a robotic manipulator The proposed RNLAR technique can compensate for the effects of model-plan-mismatch (MPM) and process disturbance. A nonlinear primary residual vectors (PRV) design method to detect faults is proposed where the PRVs are highly sensitive to faults and less sensitive to MPM and process disturbance. Experimental results on a PUMA 560 are presented to justify the effectiveness of the RNLAR scheme.