Glowworm-inspired robot swarm for simultaneous taxis towards multiple radiation sources

This paper presents a glowworm metaphor based distributed algorithm that enables a collection of minimalist mobile robots to split into subgroups, exhibit simultaneous taxis-behavior towards, and rendezvous at multiple radiation sources such as nuclear/hazardous chemical spills and fire-origins in a fire calamity. The algorithm is based on a glowworm swarm optimization (GSO) technique that finds multiple optima of multimodal functions. The algorithm is in the same spirit as the ant-colony optimization (ACO) algorithms, but with several significant differences. The agents in the glowworm algorithm carry a luminescence quantity called luciferin along with them. Agents are thought of as glowworms that emit a light whose intensity is proportional to the associated luciferin. The key feature that is responsible for the working of the algorithm is the use of an adaptive local-decision domain, which we use effectively to detect the multiple source locations of interest. The glowworms have a finite sensor range which defines a hard limit on the local-decision domain used to compute their movements. Extensive simulations validate the feasibility of applying the glowworm algorithm to the problem of multiple source localization. We build four wheeled robots called glowworms to conduct our experiments. We use a preliminary experiment to demonstrate the basic behavioral primitives that enable each glowworm to exhibit taxis behavior towards source locations and later demonstrate a sound localization task using a set of four glowworms.

An SIMD machine for low-level vision

This paper presents an SIMD machine which has been tuned to execute low-level vision algorithms employing the relaxation labeling paradigm. Novel features of the design include: 1. (1) a communication scheme capable of window accessing under a single instruction. 2. (2) flexible I/O instructions to load overlapped data segments; and 3. (3) data-conditional instructions which can be nested to an arbitrary degree. A time analysis of the stereo correspondence problem, as implemented on a simulated version of the machine using the probabilistic relaxation technique, shows a speed up of almost N2 for an N × N array of PEs.

Miniature Compliant Grippers With Vision-Based Force Sensing

This paper is concerned with grasping biological cells in aqueous medium with miniature grippers that can also help estimate forces using vision-based displacement measurement and computation. We present the design, fabrication, and testing of three single-piece, compliant miniature grippers with parallel and angular jaw motions. Two grippers were designed using experience and intuition, while the third one was designed using topology optimization with implicit manufacturing constraints. These grippers were fabricated using different manufacturing techniques using spring steel and polydimethylsiloxane ( PDMS). The grippers also serve the purpose of a force sensor. Toward this, we present a vision-based force-sensing technique by solving Cauchy's problem in elasticity using an improved algorithm. We validated this technique at the macroscale, where there was an independent method to estimate the force. In this study, the gripper was used to hold a yeast ball and a zebrafish egg cell of less than 1 mm in diameter. The forces involved were estimated to be about 30 and 10 mN for the yeast ball and the zebrafish egg cell, respectively.

Dynamical Resolution of Redundancy for Robot Manipulators

A large class of work in the robot manipulator literature deals with the kinematical resolution of redundancy based on the pseudo-inverse of the manipulator Jacobian. In this paper an alternative dynamical approach to redundancy resolution is developed which utilizes the mapping between the actuator torques and the acceleration of the end-effector, at a given dynamic state of the manipulator. The potential advantages of the approach are discussed and an example of a planar 3R manipulator following a circular end-effector trajectory is used to illustrate the proposed approach as well as to compare it with the more well-known approach based on the pseudo-inverse.

An Efficient Random Walk Strategy for Sampling Based Robot Motion Planners

Sampling based planners have been successful in path planning of robots with many degrees of freedom, but still remains ineffective when the configuration space has a narrow passage. We present a new technique based on a random walk strategy to generate samples in narrow regions quickly, thus improving efficiency of Probabilistic Roadmap Planners. The algorithm substantially reduces instances of collision checking and thereby decreases computational time. The method is powerful even for cases where the structure of the narrow passage is not known, thus giving significant improvement over other known methods.

Some aspects of information processing in biological vision

An attempt is made to present some challenging problems (mainly to the technically minded researchers) in the development of computational models for certain (visual) processes which are executed with, apparently, deceptive ease by the human visual system. However, in the interest of simplicity (and with a nonmathematical audience in mind), the presentation is almost completely devoid of mathematical formalism. Some of the findings in biological vision are presented in order to provoke some approaches to their computational models, The development of ideas is not complete, and the vast literature on biological and computational vision cannot be reviewed here. A related but rather specific aspect of computational vision (namely, detection of edges) has been discussed by Zucker, who brings out some of the difficulties experienced in the classical approaches.Space limitations here preclude any detailed analysis of even the elementary aspects of information processing in biological vision, However, the main purpose of the present paper is to highlight some of the fascinating problems in the frontier area of modelling mathematically the human vision system.

Role of feedback in mammalian vision: a new hypothesis and a computational model

This paper presents a novel hypothesis on the function of massive feedback pathways in mammalian visual systems. We propose that the cortical feature detectors compete not for the right to represent the output at a point, but for exclusive rights to abstract and represent part of the underlying input. Feedback can do this very naturally. A computational model that implements the above idea for the problem of line detection is presented and based on that we suggest a functional role for the thalamo-cortical loop during perception of lines. We show that the model successfully tackles the so called Cross problem. Based on some recent experimental results, we discuss the biological plausibility of our model. We also comment on the relevance of our hypothesis (on the role of feedback) to general sensory information processing and recognition. (C) 1998 Published by Elsevier Science Ltd. All rights reserved.

A Flexure-based Deployable Stereo Vision Mechanism and Temperature and Force Sensors for Laparoscopic Tools

This paper presents concepts, designs, and working prototypes of enhanced laparoscopic surgical tools. The enhancements are in equipping the tool with force and temperature sensing as well as image acquisition for stereo vision. Just as the pupils of our eyes are adequately spaced out and the distance between them is adjustable, two minute cameras mounted on a mechanism in our design can be moved closer or farther apart inside the inflated abdomen during the surgery. The cameras are fitted to a deployable mechanism consisting of flexural joints so that they can be inserted through a small incision and then deployed and moved as needed.A temperature sensor and a force sensor are mounted on either of the gripping faces of the surgical grasping tool to measure the temperature and gripping force, which need to be controlled for safe laparoscopic surgery. The sensors are small enough and hence they do not cause interference during surgery and insertion.Prototyping and working of the enhanced laparoscopic tool are presented with details

A vision modeling framework for DHM using geometrically estimated FoV

Digital human modeling (DHM) involves modeling of structure, form and functional capabilities of human users for ergonomics simulation. This paper presents application of geometric procedures for investigating the characteristics of human visual capabilities which are particularly important in the context mentioned above. Using the cone of unrestricted directions through the pupil on a tessellated head model as the geometric interpretation of the clinical field-of-view (FoV), the results obtained are experimentally validated. Estimating the pupil movement for a given gaze direction using Listing's Law, FoVs are re-computed. Significant variation of the FoV is observed with the variation in gaze direction. A novel cube-grid representation, which integrated the unit-cube representation of directions and the enhanced slice representation has been introduced for fast and exact point classification for point visibility analysis for a given FoV. Computation of containment frequency of every grid-cell for a given set of FoVs enabled determination of percentile-based FoV contours for estimating the visual performance of a given population. This is a new concept which makes visibility analysis more meaningful from ergonomics point-of-view. The algorithms are fast enough to support interactive analysis of reasonably complex scenes on a typical desktop computer. (C) 2011 Elsevier Ltd. All rights reserved.