Dynamic Active Constraints for Surgical Robots using Vector Field Inequalities

Robotic assistance allows surgeons to perform dexterous and tremor-free procedures, but robotic aid is still underrepresented in procedures with constrained workspaces, such as deep brain neurosurgery and endonasal surgery. In these procedures, surgeons have restricted vision to areas near the surgical tooltips, which increases the risk of unexpected collisions between the shafts of the instruments and their surroundings. In this work, our vector-field-inequalities method is extended to provide dynamic active-constraints to any number of robots and moving objects sharing the same workspace. The method is evaluated with experiments and simulations in which robot tools have to avoid collisions autonomously and in real-time, in a constrained endonasal surgical environment. Simulations show that with our method the combined trajectory error of two robotic systems is optimal. Experiments using a real robotic system show that the method can autonomously prevent collisions between the moving robots themselves and between the robots and the environment. Moreover, the framework is also successfully verified under teleoperation with tool-tissue interactions.Comment: Accepted on T-RO 2019, 19 Page

An integrated dexterous robotic testbed for space applications

An integrated dexterous robotic system was developed as a testbed to evaluate various robotics technologies for advanced space applications. The system configuration consisted of a Utah/MIT Dexterous Hand, a PUMA 562 arm, a stereo vision system, and a multiprocessing computer control system. In addition to these major subsystems, a proximity sensing system was integrated with the Utah/MIT Hand to provide capability for non-contact sensing of a nearby object. A high-speed fiber-optic link was used to transmit digitized proximity sensor signals back to the multiprocessing control system. The hardware system was designed to satisfy the requirements for both teleoperated and autonomous operations. The software system was designed to exploit parallel processing capability, pursue functional modularity, incorporate artificial intelligence for robot control, allow high-level symbolic robot commands, maximize reusable code, minimize compilation requirements, and provide an interactive application development and debugging environment for the end users. An overview is presented of the system hardware and software configurations, and implementation is discussed of subsystem functions

Using humanoid robots to study human behavior

Our understanding of human behavior advances as our humanoid robotics work progresses-and vice versa. This team's work focuses on trajectory formation and planning, learning from demonstration, oculomotor control and interactive behaviors. They are programming robotic behavior based on how we humans “program” behavior in-or train-each other

Application of JXTA-overlay platform for secure robot control

In this paper, we present the evaluation and experimental results of secured robot control in a P2P system. The control system is based on JXTA-Overlay platform. We used secure primitives and functions of JXTA-Overlay for the secure control of the robot motors. We investigated the time of robot control for some scenarios with different number of peers connected in JXTA-Overlay network. All experiments are realised in a LAN environment. The experimental results show that with the join of other peers in the network, the average time of robot control is increased, but the difference between the secure and unsecure robot control average time is nearly the samePeer ReviewedPostprint (published version

Introduction: The Third International Conference on Epigenetic Robotics

This paper summarizes the paper and poster contributions to the Third International Workshop on Epigenetic Robotics. The focus of this workshop is on the cross-disciplinary interaction of developmental psychology and robotics. Namely, the general goal in this area is to create robotic models of the psychological development of various behaviors. The term "epigenetic" is used in much the same sense as the term "developmental" and while we could call our topic "developmental robotics", developmental robotics can be seen as having a broader interdisciplinary emphasis. Our focus in this workshop is on the interaction of developmental psychology and robotics and we use the phrase "epigenetic robotics" to capture this focus

Towards a framework to make robots learn to dance

A key motive of human-robot interaction is to make robots and humans interact through different aspects of the real world. As robots become more and more realistic in appearance, so has the desire for them to exhibit complex behaviours. A growing area of interest in terms of complex behaviour is robot dancing. Dance is an entertaining activity that is enjoyed either by being the performer or the spectator. Each dance contain fundamental features that make-up a dance. It is the curiosity for some researchers to model such an activity for robots to perform in human social environments. From current research, most dancing robots are pre-programmed with dance motions and few have the ability to generate their own dance or alter their movements according to human responses while dancing. This thesis explores the question Can a robot learn to dance? . A dancing framework is proposed to address this question. The Sarsa algorithm and the Softmax algorithm from traditional reinforcement learning form part of the dancing framework to enable a virtual robot learn and adapt to appropriate dance behaviours. The robot follows a progressive approach, utilising the knowledge obtained at each stage of its development to improve the dances that it generates. The proposed framework addresses three stages of development of a robot s dance: learning ability; creative ability of dance motions, and adaptive ability to human preferences. Learning ability is the ability to make a robot gradually perform the desired dance behaviours. Creative ability is the idea of the robot generating its own dance motions, and structuring them into a dance. Adaptive ability is where the robot changes its dance in response to human feedback. A number of experiments have been conducted to explore these challenges, and verified that the quality of the robot dance can be improved through each stage of the robot s development

Multiparty motion coordination: from choreographies to robotics programs

We present a programming model and typing discipline for complex multi-robot coordination programming. Our model encompasses both synchronisation through message passing and continuous-time dynamic motion primitives in physical space. We specify continuous-time motion primitives in an assume-guarantee logic that ensures compatibility of motion primitives as well as collision freedom. We specify global behaviour of programs in a choreographic type system that extends multiparty session types with jointly executed motion primitives, predicated refinements, as well as a separating conjunction that allows reasoning about subsets of interacting robots. We describe a notion of well-formedness for global types that ensures motion and communication can be correctly synchronised and provide algorithms for checking well-formedness, projecting a type, and local type checking. A well-typed program is communication safe, motion compatible, and collision free. Our type system provides a compositional approach to ensuring these properties. We have implemented our model on top of the ROS framework. This allows us to program multi-robot coordination scenarios on top of commercial and custom robotics hardware platforms. We show through case studies that we can model and statically verify quite complex manoeuvres involving multiple manipulators and mobile robots---such examples are beyond the scope of previous approaches