Autonomous Morphogenesis in Self-assembling Robots Using IR-Based Sensing and Local Communications

This paper presents a simple decentralised morphology control mechanism for a swarm of self-assembling robots. Each robot in the system is fully autonomous and controlled using a behaviour-based approach with only infrared-based local sensing and communications. A graph-based recruitment strategy is proposed to guide the growth of 2D planar organisms, and local communications are used to self-organise the behaviours of robots during the morphogenesis process. The effectiveness of the approach has been verified, in simulation, for a diverse set of target structures. © 2010 Springer-Verlag Berlin Heidelberg

Modelling a wireless connected swarm of mobile robots

It is a characteristic of swarm robotics that modelling the overall swarm behaviour in terms of the low-level behaviours of individual robots is very difficult. Yet if swarm robotics is to make the transition from the laboratory to real-world engineering realisation such models would be critical for both overall validation of algorithm correctness and detailed parameter optimisation. We seek models with predictive power: models that allow us to determine the effect of modifying parameters in individual robots on the overall swarm behaviour. This paper presents results from a study to apply the probabilistic modelling approach to a class of wireless connected swarms operating in unbounded environments. The paper proposes a probabilistic finite state machine (PFSM) that describes the network connectivity and overall macroscopic behaviour of the swarm, then develops a novel robot-centric approach to the estimation of the state transition probabilities within the PFSM. Using measured data from simulation the paper then carefully validates the PFSM model step by step, allowing us to assess the accuracy and hence the utility of the model. © Springer Science + Business Media, LLC 2008

Plan Library Reconfigurability in BDI Agents

One of the major advantages of modular architectures in robotic systems is the ability to add or replace nodes, without needing to rearrange the whole system. In this type of system, autonomous agents can aid in the decision making and high-level control of the robot. However, when autonomously replacing a node it can be difficult to reconfigure plans in the agent's plan library while retaining correctness. In this paper, we exploit the formal concept of capabilities in Belief-Desire-Intention agents and describe how agents can reason about these capabilities in order to reconfigure their plan library while retaining overall correctness constraints. To validate our approach, we show the implementation of our framework and an experiment using a practical example in the Mars rover scenario