Real-time active constraint generation and enforcement for surgical tools using 3D detection and localisation network - Souipas, Spyridon; Nguyen, Anh; Laws, Stephen G.; Davies, Brian L.; Rodriguez y Baena, Ferdinando (Frontiers in Robotics and AI, 2024)
Collaborative robots, designed to work alongside humans for manipulating end-effectors, greatly benefit from the implementation of active constraints. This process comprises the definition of a boundary, followed by the enforcement of some control algorithm when the robot tooltip interacts with the generated boundary. Contact with the constraint boundary is communicated to the human operator through various potential forms of feedback. In fields like surgical robotics, where patient safety is paramount, implementing active constraints can prevent the robot from interacting with portions of the patient anatomy that shouldn't be operated on. Despite improvements in orthopaedic surgical robots, however, there exists a gap between bulky systems with haptic feedback capabilities and miniaturised systems that only allow for boundary control, where interaction with the active constraint boundary interrupts robot functions. Generally, active constraint generation relies on optical tracking systems and preoperative imaging techniques. This paper presents a refined version of the Signature Robot, a three degrees-of-freedom, hands-on collaborative system for orthopaedic surgery. Additionally, it presents a method for generating and enforcing active constraints "on-the-fly" using our previously introduced monocular, RGB, camerabased network, SimPS-Net. The network success rate, defined as the ratio of correct over total object localisation results, was calculated to be 54.7% ± 5.2% while defining the boundary. This boundary was subsequently used for constraint enforcement testing. The robot was utilised to test two different active constraints: a safe region and a restricted region. In the safe region case, haptic feedback resisted tooltip manipulation beyond the active constraint boundary, with a mean distance from the boundary of 2.70mm ± 0.37mm and a mean exit duration of 0.76s ± 0.11s.For the restricted-zone constraint, the operator was successfully prevented from penetrating the boundary in 100% of attempts. This paper showcases the viability of the proposed robotic platform and presents promising results of a versatile constraint generation and enforcement pipeline.