In the future, human-robot interaction will include collaboration in close-quarters where the environment geometry is partially unknown. As a means for enabling such interaction, this paper presents a multi-modal sensor array capable of contact detection and localization, force sensing, proximity sensing, and mapping. The sensor array integrates Hall effect and time-of-flight (ToF) sensors in an I2C communication network. The design, fabrication, and characterization of the sensor array for a future in-situ collaborative continuum robot are presented. Possible perception benefits of the sensor array are demonstrated for accidental contact detection, mapping of the environment, selection of admissible zones for bracing, and constrained motion control of the end effector while maintaining a bracing constraint with an admissible rolling motion.

Current multi-backbone continuum robots are limited to a constant cross-sectional diameter. This paper proposes a design alternative that overcomes this limitation. The ability to change the diameter of a continuum robot expands the repertoire of kinematic redundancy and enables kinematic parameter adaptation to optimize performance. A continuum robot design based on the angulated scissor mechanism is presented along with its position analysis. An exploration of admissible design parameter values for a given continuum robot segment with a desired maximum curvature while maintaining an open bore along its center is also carried out. A design presenting how this mechanism can be incorporated into a continuum robot is shown and a strategy for minimizing joint forces and avoiding joint limits is formulated as a gradient descent redundancy resolution problem in a simulation case study. The simulation results show that varying the diameter can significantly reduce joint forces while preserving the workspace and avoiding joint limits. This work is a first step towards continuum robots with situational awareness that will use their sensing capabilities to adapt their structure in order to optimize task execution performance.