A Comparison of Different Cognitive Paradigms Using Simple Animats in a Virtual Laboratory, with Implications to the Notion of Cognition

In this thesis I present a virtual laboratory which implements five different models for controlling animats: a rule-based system, a behaviour-based system, a concept-based system, a neural network, and a Braitenberg architecture. Through different experiments, I compare the performance of the models and conclude that there is no best model, since different models are better for different things in different contexts. The models I chose, although quite simple, represent different approaches for studying cognition. Using the results as an empirical philosophical aid, I note that there is no best approach for studying cognition, since different approaches have all advantages and disadvantages, because they study different aspects of cognition from different contexts. This has implications for current debates on proper approaches for cognition: all approaches are a bit proper, but none will be proper enough. I draw remarks on the notion of cognition abstracting from all the approaches used to study it, and propose a simple classification for different types of cognition

Autonomous vehicles that care for houseplants

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2004.Includes bibliographical references (p. 91-95).Robotany is a system of autonomous robots that act on behalf of houseplants that rest on top of their chassis. Their duty is to do what plants would if they had the gift of mobility - namely to seek out sunlight or water when there are insufficient amounts of either at their current location. Despite the specialized application, the underlying framework of the robots is rather general and can be used in a variety of situations. The robots are designed to be easily modifiable for a given application. They are constructed using rapid-prototyping techniques that allow them to be built quickly and The software controlling Robotany utilizes a behavior-based approach, one that takes its cue from nature's solutions to problems facing any mobile being. It follows Braitenberg's model for seeking out light in an implicit manner. A new approach to obstacle avoidance is used, based on reactance to in situ sensor readings and a simplified internal map of the local environment. Robotany also incorporates a simple homeostatic system to regulate the quality of its behaviors and to determine when one behavior should take precedence over another. inexpensively. A novel design is utilized for the vehicle's suspension. This design is far simpler, cheaper, and more easily customized than traditional systems that perform the same task. The software controlling Robotany utilizes a behavior-based approach, one that takes its cue from nature's solutions to problems facing any mobile being. It follows Braitenberg's model for seeking out light in an implicit manner. A new approach to obstacle avoidance is used, based on reactance to in situ sensor readings and a simplified internal map of the local environment. Robotany also incorporates a simple homeostatic system to regulate the quality(cont.) of its behaviors and to determine when one behavior should take precedence over another. Experimental results presented in this thesis show that the robots are successful in finding sources of light while avoiding obstacles in their path.by Sara Elizabeth Cinnamon.S.M

Learning and Co-operation in Mobile Multi-Robot Systems

Merged with duplicate record 10026.1/1984 on 27.02.2017 by CS (TIS)This thesis addresses the problem of setting the balance between exploration and exploitation in teams of learning robots who exchange information. Specifically it looks at groups of robots whose tasks include moving between salient points in the environment. To deal with unknown and dynamic environments,such robots need to be able to discover and learn the routes between these points themselves. A natural extension of this scenario is to allow the robots to exchange learned routes so that only one robot needs to learn a route for the whole team to use that route. One contribution of this thesis is to identify a dilemma created by this extension: that once one robot has learned a route between two points, all other robots will follow that route without looking for shorter versions. This trade-off will be labeled the Distributed Exploration vs. Exploitation Dilemma, since increasing distributed exploitation (allowing robots to exchange more routes) means decreasing distributed exploration (reducing robots ability to learn new versions of routes), and vice-versa. At different times, teams may be required with different balances of exploitation and exploration. The main contribution of this thesis is to present a system for setting the balance between exploration and exploitation in a group of robots. This system is demonstrated through experiments involving simulated robot teams. The experiments show that increasing and decreasing the value of a parameter of the novel system will lead to a significant increase and decrease respectively in average exploitation (and an equivalent decrease and increase in average exploration) over a series of team missions. A further set of experiments show that this holds true for a range of team sizes and numbers of goals

Individuals cultivating edible plants on buildings in England

Food production, particularly local production, is a key component of sustainable urban environments, given the resilience of the supply and disposal of food are major concerns in cities worldwide. Due to the lack of land for food production in dense urban areas, people have explored possibilities for food production on walls, rooftops, balconies, windowsills and inside buildings. The technology for the integration of food production on buildings is continuously being developed, where plant and building technology have been the main focus. But at present there is a lack of understanding about the users of such technology and how they relate to systems for cultivating edible plants on buildings. This work attempts to fill this gap in understanding, examining a primary research question: “What affects individuals to cultivate edible plants on buildings in England?” To this end, this research utilizes a two-phase sequential mixed method. In phase 1, a questionnaire was formed to test hypotheses based on the Behaviour Change Wheel (BCW), behaviour theory. In phase 2, semi-structured interviews were undertaken in order to further explore the findings of phase 1. Primary data were collected from 65 participants who completed Surveys in phase 1 of the research, and in phase 2 from 30 interviewees from England who have varying levels of experience of cultivating edible plants and/or cultivating edible plants on buildings. Findings identified forty-one parameters that affect the behaviour to cultivate edible plants on buildings. These parameters offer a comprehensive framework for understanding what affects users to cultivate edible plants on buildings. They highlight that the following are important for an individual to cultivate edible plants on buildings; cognitive capacity available to implement and maintain the system, knowledge of how and why to cultivate edible plants on buildings, motivation to cultivate edible plants on a building, the outcomes obtained from undertaking the behaviour and the individual’s community. These parameters were further conceptually linked with constructs from two behaviour theories (the Theory of Planned Behaviour and BCW), links that lent further validity and theoretical reach to these data. Parameters were also linked to intervention functions and policy categories from BCW in order to explore how they can be addressed, indicating that education, training and modelling are key interventions that can help promote behaviour. This research offers a framework for understanding the parameters that affect individuals to cultivate edible plants on buildings. This knowledge can be used in the development of technologies for cultivating edible plants on buildings and the implementation of these systems, where the relevant parameters can be established on a case-by-case basis for the target users. This research also contributes new empirical knowledge to the behaviour theories and their application, and offers ideas for practical interventions

Mobile Robots

The objective of this book is to cover advances of mobile robotics and related technologies applied for multi robot systems' design and development. Design of control system is a complex issue, requiring the application of information technologies to link the robots into a single network. Human robot interface becomes a demanding task, especially when we try to use sophisticated methods for brain signal processing. Generated electrophysiological signals can be used to command different devices, such as cars, wheelchair or even video games. A number of developments in navigation and path planning, including parallel programming, can be observed. Cooperative path planning, formation control of multi robotic agents, communication and distance measurement between agents are shown. Training of the mobile robot operators is very difficult task also because of several factors related to different task execution. The presented improvement is related to environment model generation based on autonomous mobile robot observations

Coupling Movement Primitives: Interaction With the Environment and Bimanual Tasks

The framework of dynamic movement primitives (DMPs) contains many favorable properties for the execution of robotic trajectories, such as indirect dependence on time, response to perturbations, and the ability to easily modulate the given trajectories, but the framework in its original form remains constrained to the kinematic aspect of the movement. In this paper, we bridge the gap to dynamic behavior by extending the framework with force/torque feedback. We propose and evaluate a modulation approach that allows interaction with objects and the environment. Through the proposed coupling of originally independent robotic trajectories, the approach also enables the execution of bimanual and tightly coupled cooperative tasks. We apply an iterative learning control algorithm to learn a coupling term, which is applied to the original trajectory in a feed-forward fashion and, thus, modifies the trajectory in accordance to the desired positions or external forces. A stability analysis and results of simulated and real-world experiments using two KUKA LWR arms for bimanual tasks and interaction with the environment are presented. By expanding on the framework of DMPs, we keep all the favorable properties, which is demonstrated with temporal modulation and in a two-agent obstacle avoidance task

Root-to-shoot communication for the coding of object thickness in pea plants

Plants characterized by a weak steam, such as climbing plants, need to find a potential support (i.e., a stick or a wooden trunk) to reach the greatest light exposure. Since Darwin’s observation, several studies on the searching and attachment behaviors of climbing plants have reported the unique ability of climbing plants to process different support features as to modulate their movement accordingly. Nevertheless, the strategies underlying this ability have yet to be uncovered. The present research tries to fill this gap by investigating how the interaction between the above- (i.e., stem, tendril, …) and below-ground (i.e., the root system) plant’s organs is played out in the kinematics of the approach to grasp movement. The movement of pea plants (Pisum sativum L.) toward a stimulus characterized by different thicknesses with respect to the below- and above-ground part of it (i.e., perturbed conditions) was assessed by means of three-dimensional (3D) kinematical analysis. Control conditions, in which one-thickness stimulus (i.e., thin, or thick) was presented, were also considered. Results suggest the contribution of the root system in sensing, coding, and processing below-ground information and how such information is evaluated and eventually modified at the level of the aerial part of the plant to fulfill the end-goal of the movement. Results are discussed in terms of a functional equilibrium reached through a crosstalk between the grounded and the aerial components of the plant.Plants characterized by a weak steam, such as climbing plants, need to find a potential support (i.e., a stick or a wooden trunk) to reach the greatest light exposure. Since Darwin’s observation, several studies on the searching and attachment behaviors of climbing plants have reported the unique ability of climbing plants to process different support features as to modulate their movement accordingly. Nevertheless, the strategies underlying this ability have yet to be uncovered. The present research tries to fill this gap by investigating how the interaction between the above- (i.e., stem, tendril, …) and below-ground (i.e., the root system) plant’s organs is played out in the kinematics of the approach to grasp movement. The movement of pea plants (Pisum sativum L.) toward a stimulus characterized by different thicknesses with respect to the below- and above-ground part of it (i.e., perturbed conditions) was assessed by means of three-dimensional (3D) kinematical analysis. Control conditions, in which one-thickness stimulus (i.e., thin, or thick) was presented, were also considered. Results suggest the contribution of the root system in sensing, coding, and processing below-ground information and how such information is evaluated and eventually modified at the level of the aerial part of the plant to fulfill the end-goal of the movement. Results are discussed in terms of a functional equilibrium reached through a crosstalk between the grounded and the aerial components of the plant

Extended plant cognition: a critical consideration of the concept

Within the framework of studies of plants as cognitive organisms, there is a hypothesis that plant cognitive processes are not enclosed within their bodies but extend to the environment. The extended plant cognition (EPC) hypothesis suggests that when plants modify the environment around them through the release of volatile organic compounds (VOCs), root exudates, and the sustenance of mycorrhizal networks, they extend their sensorial apparatus and externalize a part of their information-processing system. As a result, a plant can no longer be seen as an isolated organism easily distinguishable from its milieu. In this article, we discuss the implications of understanding plants as extended cognitive organisms and assess four test cases that corroborate the EPC hypothesis, one for each possible channel of extended plant cognition discussed here. We conclude that this new approach can redefine how we understand plants and their environment. EPC may also be a fruitful source of inspiration to develop new techniques in agriculture by enhancing the external elements of plant cognition

Bio-Inspired Robotics

Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field