There are many applications and tasks in which the precise, high-fidelity haptic display of deforming objects is required. A crucial element in haptic rendering is the definition of a proxy pose that follows the motion of the user, while respecting the geometry of the object being displayed. Conventional methods for computing the dynamics of a proxy interacting with a deforming object suffer from several issues relating to numerical instabilities when the proxy becomes over-constrained and high computational demands. This paper presents a novel hybrid proxy that combines modified versions of constraint-based and penalty-based proxies together to give high fidelity rendering with reduced computational requirements and enhanced robustness to situations where the proxy becomes enclosed. Experimental analysis of the proposed method shows that it can efficiently compute proxy dynamics that faithfully render the required object. This research forms a basis for further development of novel hybrid dynamic proxies for haptics and allows for increasingly complex deforming geometries to be rendered.

In hands-on robotic surgery, the surgical tool is mounted on the end-effector of a robot and is directly manipulated by the surgeon. This simultaneously exploits the strengths of both humans and robots, such that the surgeon directly feels tool–tissue interactions and remains in control of the procedure, while taking advantage of the robot's higher precision and accuracy. A crucial challenge in hands-on robotics for delicate manipulation tasks, such as surgery, is that the user must interact with the dynamics of the robot at the end-effector, which can reduce dexterity and increase fatigue. This paper presents a null-space-based optimization technique for simultaneously minimizing the mass and friction of the robot that is experienced by the surgeon. By defining a novel optimization technique for minimizing the projection of the joint friction onto the end-effector, and integrating this with our previous techniques for minimizing the belted mass/inertia as perceived by the hand, a significant reduction in dynamics felt by the user is achieved. Experimental analyses in both simulation and human user trials demonstrate that the presented method can reduce the user-experienced dynamic mass and friction by, on average, 44% and 41%, respectively. The results presented robustly demonstrate that optimizing a robots pose can result in a more natural tool motion, potentially allowing future surgical robots to operate with increased usability, improved surgical outcomes, and wider clinical uptake.

Physical human–robot interaction is fundamental to exploiting the capabilities of robots in tasks and environments where robots have limited cognition or comprehension and is virtually ubiquitous for robotic manipulation in highly unstructured environments, as are found in surgery. A critical aspect of physical human–robot interaction in these cases is controlling the robot so that the individual human and robot competencies are maximized, while guaranteeing user, task, and environment safety. Dissipative control precludes dangerous forcing of a shared tool by the robot, ensuring safety; however, it typically suffers from poor control fidelity, resulting in reduced task accuracy. In this study, a novel, rigorously formalized,$n$-dimensional dissipative control strategy is proposed that employs a new technique called “energy redirection” to generate control forces with increased fidelity while remaining dissipative and safe. Experimental validation of the method, for complete pose control, shows that it achieves a 90% reduction in task error compared with the current state of the art in dissipative control for the tested applications. The findings clearly demonstrate that the method significantly increases the fidelity and efficacy of dissipative control during physical human–robot interaction. This advancement expands the number of tasks and environments into which safe physical human–robot interaction can be employed effectively.

Active constraints and virtual fixtures are popular control strategies used within human-robot collaborative manipulation tasks, particularly in the field of robot-assisted surgery. Recent research has shown how active constraints, which robotically regulate the motion of a tool that is primarily manipulated by a human, can be implemented in dynamic environments which change and deform throughout a procedure. In a dynamic environment, movement of the constraint boundary can cause active forcing of the surgical tools, potentially reducing the surgeon's control and jeopardising patient safety. Dynamic frictional constraints have been proposed as a method for enforcing dynamic active constraints which do not generate energy of their own, and simply dissipate or redirect the energy of the surgeon to provide assistance. In this paper, dynamic frictional constraints are reformulated to allow formal proof that they are indeed dissipative, and hence also passive. This new formulation is then extended such that dynamic frictional constraints can simultaneously constrain the position and orientation of a tool. Experimental results show that the method is of significant benefit in performing a dynamic task when compared to cases without any assistance; with position and orientation constraints individually and with a conventional frictional constraint without energy redirection.

Active constraints, also known as virtual fixtures, are high-level control algorithms which can be used to assist a human in man-machine collaborative manipulation tasks. The active constraint controller monitors the robotic manipulator with respect to the environment and task, and anisotropically regulates the motion to provide assistance. The type of assistance offered by active constraints can vary, but they are typically used to either guide the user along a task-specific pathway or limit the user to within a “safe” region. There are several diverse methods described within the literature for applying active constraints, and these are surveyed within this paper. The active constraint research is described and compared using a simple generalized framework, which consists of three primary processes: 1) constraint definition, 2) constraint evaluation, and 3) constraint enforcement. All relevant research approaches for each of these processes, found using search terms associated to “virtual fixture,” “active constraint” and “motion constraint,” are presented.

Collaborative, as opposed to autonomous, control strategies are used within the majority of commercially available, surgical robotic systems. Amongst these, active constraints and virtual fixtures, where assistance is in the form of regulation applied to the motion of surgical tools, offer an effective means to maximise both user and robot capabilities. Conventional active constraint approaches, however, are likely to result in active forcing of the tools when used within a dynamically changing surgical environment. It is posited that such behaviour inherently reduces a surgeon's control over the procedure, and therefore compromises patient safety and clinical acceptance. Utilising a friction model to enforce constraints ensures that energy is never introduced into the system; however frictional constraints suffer from problems once penetration of a constrained region has occurred. A frictional constraint formulation is proposed which eliminates this by redirecting a user's motion, guiding him towards the surface. Experimental validation shows that the proposed constraint significantly improves a user's path-following performance over unassisted cases, while approaching the performance benchmark of a viscoelastic active constraint.

This paper outlines work on the development of a novel programmable rotary brake which can restrict motion of a mechanism moving in one direction whilst allowing free motion in other directions. The design, implementation and performance of a fully functional prototype are described along the work on incorporating the prototype into a 3 Degrees-Of-Freedom (DOF) haptic device. The ability of the haptic device to constrain the motion of the end-effector to point-constraint was investigated and the experiments have shown that the haptic device can implement virtual constraints without the need for a force sensor. The experiments also show that when an advanced control scheme is used the virtual wall is not felt as “sticky”.