Therapies targeting neurodegenerative diseases via brain ventricles and spinal parenchyma face delivery challenges. Systemic administration is ineffective due to the blood-brain barrier, while direct surgical access, especially for multi-site delivery, is highly invasive. The spinal subarachnoid space offers potential for microcatheter-based delivery, but existing robotic catheter technologies are unsuitable due to spinal anatomy constraints. This paper presents a miniaturised and sensorised steerable eversion-growing robot tailored to navigation of the subarachnoid space of the spine. The property of eversion reduces interaction forces with the anatomy, rendering our approach safer than microcatheters that need to be pushed. Our system is capable of real-time tip force estimation with three degrees of freedom (DoF) using fibre Bragg gratings (FBG). Additionally, it incorporates a micro-endoscope and a steerable tip, all within a tiny 2mm outer diameter. The system’s navigation, sensing, and imaging capabilities were evaluated using a realistic up-scaled phantom of the subarachnoid space covering the cervical spine, demonstrating interaction forces within the safe range of 2-5N during phantom navigation. Comparison study of instrument-tissue interactions further approved its clinical relevance, presenting a 73.78% decrease of the mean absolute forces to traditional insertion without the sheath in global measurements.

Minimally Invasive Surgery (MIS) reduces surgical risks and recovery times by enabling precise interventions around lesion sites. However, accessing these sites requires flexible instruments, which often compromise the precision afforded by rigid devices. This study proposes a thermally drawn fiber-based, tendon-driven soft robotic instrument with a two-stage hybrid motion control framework to enhance accuracy. Several learning-based inverse kinematic (IK) models were developed, with the LSTM-based model showing the best performance and used to guide open-loop large-scale motion, while a closed-loop controller refines accuracy via real-time feedback. The system is validated by path-following tasks and a simulated endometrial ablation in a vaginal phantom. Results show that the IK model realizes stable open-loop control with Euclidean error below 2 mm, while hybrid control further reduces errors to below 1 mm. This combination offers a promising MIS solution with high precision in difficult-to-reach surgical sites.

Cochlear implants (CIs) can improve hearing in patients suffering from sensorineural hearing loss via an electrode array (EA) carefully inserted in the scala tympani. Current EAs can cause trauma during insertion, threatening hearing preservation; hence we proposed a pre-curved thermally drawn EA that curls into the cochlea under the influence of body temperature. However, the additional surgical skill required to insert pre-curved EAs usually produces worse surgical outcomes. Medical robots can offer an effective solution to assist surgeons in improving surgical outcomes and reducing outliers. This work proposes a collaborative approach to insert our EA where manageable tasks are automated using a vision-based system. The insertion strategy presented allowed us to insert our EA successfully. The feasibility study showed that we can insert EAs following the defined control strategy while keeping the exerted contact forces within safe levels. The teleoperated robotic system and robotic vision approach to control a self-shaping CI has thus shown potential to provide the tools for a more delicate and atraumatic approach.