Search

The vertebrate basal ganglia play an important role in action selection—the resolution of conflicts between alternative motor programs. The effective operation of basal ganglia circuitry is also known to rely on appropriate levels of the neurotransmitter dopamine. We investigated reducing or increasing the tonic level of simulated dopamine in a prior model of the basal ganglia integrated into a robot control architecture engaged in a foraging task inspired by animal behaviour. The main findings were that progressive reductions in the levels of simulated dopamine caused slowed behaviour and, at low levels, an inability to initiate movement. These states were partially relieved by increased salience levels (stronger sensory/motivational input). Conversely, increased simulated dopamine caused distortion of the robot’s motor acts through partially expressed motor activity relating to losing actions. This could also lead to an increased frequency of behaviour switching. Levels of simulated dopamine that were either significantly lower or higher than baseline could cause a loss of behavioural integration, sometimes leaving the robot in a ‘behavioral trap’. That some analogous traits are observed in animals and humans affected by dopamine dysregulation suggests that robotic models could prove useful in understanding the role of dopamine neurotransmission in basal ganglia function and dysfunction.

In developing Trustworthy Autonomous Systems (TAS), as in other domains of technology innovation and research, there is a need to make research processes and activities more accessible to external partners and to the wider public. In this article, we describe the rationale, background and potential for an Open Laboratories approach that complements current strategies in Responsible Research and Innovation and in Open Science, relating this to experience-based aspects of trust in new technologies. We also reflect on the value and benefits of robotic telepresence as an engagement tool that can provide direct access and first-person experience of research, in a manner that is scalable and safe while mitigating some environmental and health concerns.

Summary: Social robots that can interact and communicate with people are growing in popularity for use at home and in customer-service, education, and healthcare settings. Although growing evidence suggests that co-operative and emotionally aligned social robots could benefit users across the lifespan, controversy continues about the ethical implications of these devices and their potential harms. In this perspective, we explore this balance between benefit and risk through the lens of human-robot relationships. We review the definitions and purposes of social robots, explore their philosophical and psychological status, and relate research on human-human and human-animal relationships to the emerging literature on human-robot relationships. Advocating a relational rather than essentialist view, we consider the balance of benefits and harms that can arise from different types of relationship with social robots and conclude by considering the role of researchers in understanding the ethical and societal impacts of social robotics.

Generating complex, human-like behavior in a humanoid robot like the iCub requires the integration of a wide range of open source components and a scalable cognitive architecture. Hence, we present the iCub-HRI library which provides convenience wrappers for components related to perception (object recognition, agent tracking, speech recognition, and touch detection), object manipulation (basic and complex motor actions), and social interaction (speech synthesis and joint attention) exposed as a C++ library with bindings for Java (allowing to use iCub-HRI within Matlab) and Python. In addition to previously integrated components, the library allows for simple extension to new components and rapid prototyping by adapting to changes in interfaces between components. We also provide a set of modules which make use of the library, such as a high-level knowledge acquisition module and an action recognition module. The proposed architecture has been successfully employed for a complex human–robot interaction scenario involving the acquisition of language capabilities, execution of goal-oriented behavior and expression of a verbal narrative of the robot’s experience in the world. Accompanying this paper is a tutorial which allows a subset of this interaction to be reproduced. The architecture is aimed at researchers familiarizing themselves with the iCub ecosystem, as well as expert users, and we expect the library to be widely used in the iCub community.

The design and implementation of the periphery of an artificial whisker sensory system is presented. It has been developed by adopting a biomimetic approach to model the structure and function of rodent facial vibrissae. The artificial vibrissae have been formed using composite materials and have the ability to be actively moved or whisked. The sensory structures at the root of real vibrissae has been modelled and implemented using micro strain gauges and Digital Signal Processors. The primary afferents and vibrissal trigeminal ganglion have been modelled using empirical data taken from electrophysiological measurements, and implemented in real-time using a Field Programmable Gate Array. Pipelining techniques were employed to maximise the utility of the FPGA hardware. The system is to be integrated into a more complete whisker sensory model, including neural structures within the central nervous system, which can be used to orient a mobile robot.

The design and implementation of the periphery of an artificial whisker sensory system is presented. It has been developed by adopting a biomimetic approach to model the structure and function of rodent facial vibrissae. The artificial vibrissae have been formed using composite materials and have the ability to be actively moved or whisked. The sensory structures at the root of real vibrissae has been modelled and implemented using micro strain gauges and Digital Signal Processors. The primary afferents and vibrissal trigeminal ganglion have been modelled using empirical data taken from electrophysiological measurements, and implemented in real-time using a Field Programmable Gate Array. Pipelining techniques were employed to maximise the utility of the FPGA hardware. The system is to be integrated into a more complete whisker sensory model, including neural structures within the central nervous system, which can be used to orient a mobile robot.