Towards hierarchical blackboard mapping on a whiskered robot

The paradigm case for robotic mapping assumes large quantities of sensory information which allow the use of relatively weak priors. In contrast, the present study considers the mapping problem for a mobile robot, CrunchBot, where only sparse, local tactile information from whisker sensors is available. To compensate for such weak likelihood information, we make use of low-level signal processing and strong hierarchical object priors. Hierarchical models were popular in classical blackboard systems but are here applied in a Bayesian setting as a mapping algorithm. The hierarchical models require reports of whisker distance to contact and of surface orientation at contact, and we demonstrate that this information can be retrieved by classifiers from strain data collected by CrunchBot's physical whiskers. We then provide a demonstration in simulation of how this information can be used to build maps (but not yet full SLAM) in an zero-odometry-noise environment containing walls and table-like hierarchical objects. © 2012 Elsevier B.V. All rights reserved

Mapping with Sparse Local Sensors and Strong Hierarchical Priors

The paradigm case for robotic mapping assumes large quantities of sensory information which allow the use of relatively weak priors. In contrast, the present study considers the mapping problem in environments where only sparse, local sensory information is available. To compensate for these weak likelihoods, we make use of strong hierarchical object priors. Hierarchical models were popular in classical blackboard systems but are here applied in a Bayesian setting and novelly deployed as a mapping algorithm. We give proof of concept results, intended to demonstrate the algorithm’s applicability as a part of a tactile SLAM module for the whiskered SCRATCHbot mobile robot platform

The robot vibrissal system: Understanding mammalian sensorimotor co-ordination through biomimetics

Chapter 10 The Robot Vibrissal System: Understanding Mammalian Sensorimotor Co-ordination Through Biomimetics Tony J. Prescott, Ben Mitchinson, Nathan F. Lepora, Stuart P. Wilson, Sean R. Anderson, John Porrill, Paul Dean, Charles ..

Biomimetic tactile target acquisition, tracking and capture

Good performance in unstructured/uncertain environments is an ongoing problem in robotics; in biology, it is an everyday observation. Here, we model a particular biological system - hunting in the Etruscan shrew - as a case study in biomimetic robot design. These shrews strike rapidly and accurately after gathering very limited sensory information from their whiskers; we attempt to mimic this performance by using model-based simultaneous discrimination and localisation of a 'prey' robot (i.e. by using strong priors to make sense of limited sensory data), building on our existing low-level models of attention and appetitive behaviour in small mammals. We report performance that is comparable, given the spatial and temporal scale differences, to shrew performance, and discuss what this study reveals about biomimetic robot design in general. © 2013 Elsevier B.V. All rights reserved

A Blackboard-style decision-making system for multi-tier craft control and its evaluation

This article presents an approach for decision-making in support of the control of an autonomous system of multiple tiers of robots (e.g., satellite, aerial and ground) based on the Blackboard architectural style. Under the proposed approach, the system evaluates prospective approaches for goal satisfaction (identified by user selected final rules), identifies the lowest-cost solution and determines the best path to achieving the goal, via the analysis of the Blackboard rule and action set. Two different approaches to this rule and action path generation are discussed. This article presents the proposed Blackboard-style architecture for autonomous multi-tier control and describes its implementation. The benefits and drawbacks of the Blackboard-style approach are analysed, its extrapolation to the control of multiple heterogeneous craft is presented and the tradeoffs between the two approaches to rule-path generation are assessed

Algebraic approaches to artificial chemistries

We have developed a new systematic framework, MetaChemisty for the description of artificial chemistries (AChems). It encompasses existing systems. It has the flexibility and complexity to allow for new features and new systems. A joint description language will allow comparisons to be drawn between systems. This will allow us to write metrics and benchmarks for artificial chemistries. It also enables us to combine existing systems in different ways to give a wealth of more complex and varied systems. We will be able to build novel chemistries quicker through reuse of code and features between chemistries allowing new chemistries to start from a more complex base line.We have also developed an algebraic artificial chemistry, Jordan Algebra Artificial Chemistry (JA AChem). This chemistry is based on existing algebra which is leverage to ensure features such as isomers and isotopes are possible in our system. The existence of isotopes leads naturally to the existence of elements for this chemistry. It is a chemistry with both constructive and destructive reactions making it a good candidate for further study as an open-ended system.We analyse the effect of changing probabilistic processes in JA AChem by modifying the probability spawning functions that control them. We also look at the algebraic properties of these probability spawning functions. We have described Swarm Chemistry, Sayama (2009),in the MetaChem showing it is at least more expressive than the previous framework for artificial chemistries, Dittrich et al. (2001).We use the framework to combine two artificial chemistries using a simple environment link structure to produce eight new modular AChems with a modular approach. This link structure requires minimal addition to existing code for artificial chemistry systems and no modification to most modules

Maritime expressions:a corpus based exploration of maritime metaphors

This study uses a purpose-built corpus to explore the linguistic legacy of Britain’s maritime history found in the form of hundreds of specialised ‘Maritime Expressions’ (MEs), such as TAKEN ABACK, ANCHOR and ALOOF, that permeate modern English. Selecting just those expressions commencing with ’A’, it analyses 61 MEs in detail and describes the processes by which these technical expressions, from a highly specialised occupational discourse community, have made their way into modern English. The Maritime Text Corpus (MTC) comprises 8.8 million words, encompassing a range of text types and registers, selected to provide a cross-section of ‘maritime’ writing. It is analysed using WordSmith analytical software (Scott, 2010), with the 100 million-word British National Corpus (BNC) as a reference corpus. Using the MTC, a list of keywords of specific salience within the maritime discourse has been compiled and, using frequency data, concordances and collocations, these MEs are described in detail and their use and form in the MTC and the BNC is compared. The study examines the transformation from ME to figurative use in the general discourse, in terms of form and metaphoricity. MEs are classified according to their metaphorical strength and their transference from maritime usage into new registers and domains such as those of business, politics, sports and reportage etc. A revised model of metaphoricity is developed and a new category of figurative expression, the ‘resonator’, is proposed. Additionally, developing the work of Lakov and Johnson, Kovesces and others on Conceptual Metaphor Theory (CMT), a number of Maritime Conceptual Metaphors are identified and their cultural significance is discussed