Beyond Gazing, Pointing, and Reaching: A Survey of Developmental Robotics

Developmental robotics is an emerging field located at the intersection of developmental psychology and robotics, that has lately attracted quite some attention. This paper gives a survey of a variety of research projects dealing with or inspired by developmental issues, and outlines possible future directions

Capability by Stacking: The Current Design Heuristic for Soft Robots

Soft robots are a new class of systems being developed and studied by robotics scientists. These systems have a diverse range of applications including sub-sea manipulation and rehabilitative robotics. In their current state of development, the prevalent paradigm for the control architecture in these systems is a one-to-one mapping of controller outputs to actuators. In this work, we define functional blocks as the physical implementation of some discrete behaviors, which are presented as a decomposition of the behavior of the soft robot. We also use the term ‘stacking’ as the ability to combine functional blocks to create a system that is more complex and has greater capability than the sum of its parts. By stacking functional blocks a system designer can increase the range of behaviors and the overall capability of the system. As the community continues to increase the capabilities of soft systems—by stacking more and more functional blocks—we will encounter a practical limit with the number of parallelized control lines. In this paper, we review 20 soft systems reported in the literature and we observe this trend of one-to-one mapping of control outputs to functional blocks. We also observe that stacking functional blocks results in systems that are increasingly capable of a diverse range of complex motions and behaviors, leading ultimately to systems that are capable of performing useful tasks. The design heuristic that we observe is one of increased capability by stacking simple units—a classic engineering approach. As we move towards more capability in soft robotic systems, and begin to reach practical limits in control, we predict that we will require increased amounts of autonomy in the system. The field of soft robotics is in its infancy, and as we move towards realizing the potential of this technology, we will need to develop design tools and control paradigms that allow us to handle the complexity in these stacked, non-linear systems

“I spy, with my little sensor”:Fair data handling practices for robots between privacy, copyright and security

The paper suggests an amendment to Principle 4 of ethical robot design, and a demand for "transparency by design". It argues that while misleading vulnerable users as to the nature of a robot is a serious ethical issue, other forms of intentionally deceptive or unintentionally misleading aspects of robotic design pose challenges that are on the one hand more universal and harmful in their application, on the other more difficult to address consistently through design choices. The focus will be on transparent design regarding the sensory capacities of robots. Intuitive, low-tech but highly efficient privacy preserving behaviour is regularly dependent on an accurate understanding of surveillance risks. Design choices that hide, camouflage or misrepresent these capacities can undermine these strategies. However, formulating an ethical principle of "sensor transparency" is not straightforward, as openness can also lead to greater vulnerability and with that security risks. We argue that the discussion on sensor transparency needs to be embedded in a broader discussion of "fair data handling principles" for robots that involve issues of privacy, but also intellectual property rights such as copyright

RAF | A framework for symbiotic agencies in robotic – aided fabrication

The research presented in this paper utilizes industrial robotic arms and new material technologies to model and explore a different conceptual framework for ‘robotic-aided fabrication’ based on material formation processes, collaboration, and feedback loops. Robotic-aided fabrication as a performative design process needs to develop and demonstrate itself through projects that operate at a discrete level, emphasizing the role of the different agents and prioritizing their relationships over their autonomy. It encourages a process where the robot, human and material are not simply operational entities but a related whole. In the pre-actual state of this agenda, the definition and understanding of agencies and the inventory of their relations is more relevant than their implementation. Three test scenarios are described using human designers, phase-changing materials, and a six-axis industrial robotic arm with an external sensor. The common thread running through the three scenarios is the facilitation of interaction within a digital fabrication process. The process starts with a description of the different agencies and their potentiality before any relation is formed. Once the contributions of each agent are understood they start to form relations with different degrees of autonomy. A feedback loop is introduced to create negotiation opportunities that can result in a rich and complex design process. The paper concludes with speculation on the advantages and possible limitations of semi-organic design methods through the emergence of patterns of interaction between the material, machine and designer resulting in new vistas towards how design is conceived, developed, and realised

The Multiple Roles of Anticipation in Developmental Robotics

Anticipatory systems have been shown to be useful in discrete, symbolic systems. However, non­symbolic anticipatory systems are less well understood. In this paper, we explore the use of anticipation within the framework of connectionist networks to bootstrap from an innate behavior; to drive a reinforcement signal; and to provide feedback on the learnability of a task

The Multiple Roles of Anticipation in Developmental Robotics

Anticipatory systems have been shown to be useful in discrete, symbolic systems. However, non­symbolic anticipatory systems are less well understood. In this paper, we explore the use of anticipation within the framework of connectionist networks to bootstrap from an innate behavior; to drive a reinforcement signal; and to provide feedback on the learnability of a task