Biologically Inspired Computing and Robotics
Biological organisms, through the dual processes of natural selection and learning, are exquisitely adapted to survive and adapt in complex, ever-changing environments. In contrast, despite the many successes of traditional approaches to robotics, most robots are behaviourally fragile and incapable of learning or adaptation. The goal of the newly emerging area of biorobotics is to seek inspiration from biological systems to build robots with a full range of adaptable behaviours in any given environmental niche.
Most work to date has focused on building insectlike robots, although more ambitious programs of research employ human-like or anthropomorphic robots.
Our own interests in biorobotics are many and varied. Work in the Group explores ways in which artificial nervous systems could be constructed. Once constructed a fundamental problem is keeping them capable of learning and adaption, a property known as neural plasticity. Our neuronal control algorithms permit robots to learn sensory and motor maps, to represent how they and the external world are organised. Such maps are analogous to the structures found in the brains of animals and humans.
Computer simulations and real robots are used to explore these and other issues. We draw inspiration from and contribute to developments in biological neuroscience.
- Adaptive Robotics
- The goal is the construction of robots that demonstrate robust, flexible and adaptive behaviour and which learn in complex environments.
- Developmental Robotics
- Attempts are being made to outline the stages through which adaptive systems pass as they attempt to acquire basic and then more complex capabilities and behaviours.
- Synthetic Nervous Systems
- The Group is continuing the development of software and hardware that is inspired by our knowledge of how biological nervous systems are arranged and organised. The neural systems of insects can be modelled to produce simple robots demonstrating autonomous behaviour.