At CRL, we create innovative continuum robot designs with novel features such as drastically increased motion capabilities through extensibility, adjustable stiffness through scale sheaths, and higher accuracy through parallel structures.
In terms of designing continuum robots a wide spectrum of compliance and elasticity can be achieved by variation of materials, structure, actuation, etc. We aim at developing particularly small continuum robots which are able to manoeuvre and manipulate in constrained and tortuous environments.
In addition to the physical design of continuum robots, research @CRL is also concerned with computational design. For instance, we are developing evolutionary algorithms and machine learning techniques to explore the infinite parameter space of tubular continuum robots and derive design guidelines.
The theoretical foundation of traditional robots cannot be transferred directly to continuum robots. Thus far, there exist no general concepts for continuum robots, but methods for special cases and particular examples.
The CRL aims at deriving fundamental methods, definitions, and characteristics for continuum robotics as they exist in conventional robotics. To achieve this, we investigate techniques leveraging elasticity theory, differential geometry, and machine learning.
This research area is concerned with the development of efficient and real-time methods for computation, motion generation as well as task- and situation adaptive control of continuum robots. The inherent flexibility and many to infinite degrees of freedom are the main challenges for algorithm development.
This research area involves the definition of appropriate objectives. For instance, by sampling the configuration space of a tubular continuum robot and discretising the Cartesian workspace into unit volumes, it has been possible to evaluate the reachability and redundancy of this particular continuum robot type for the first time. This serves as a measure for motion planning algorithms and control.
Trajectory generation and motion planning for continuum robots requires the development of scalable algorithms to consider the degrees of freedom and underactuation. While probabilistic methods led to sufficient first results, we are investigating motion planning algorithms which consider the morphology of continuum robots in my laboratory.
Thanks to their compliance, continuum robots are inherently safe in direct contact with or in proximity to humans. As their structure is continuously bending with many degrees of freedom, the control input to the robot and the resulting shape cannot be mentally related by the operator. Additionally, continuum robots are foreseen to be deployed in-situ such that the operator looses direct sight.
At CRL, we aim at designing immersive human robot interfaces for continuum robot systems to enable intuitive interaction and collaborative manipulation. To allow for different levels of autonomy, ranging from teleoperation over task autonomy to full automation, we investigate methods to perceive, interpret, reason, and act on a situation.