The arrival of 100K+ GPU clusters marks a new frontier in AI infrastructure. Standard communication stack meets new challenges as physical topologies span multiple datacenter buildings, introducing high bandwidth-delay product links where latency increases by up to 30× compared to intra-rack traffic. Furthermore, the transition toward Mixture-of-Experts architectures generating bursty all-to-all patterns that create transient congestion hotspots. These constraints, combined with an operational environment where hardware failures shift from anomalies to frequent occurrences, renders traditionally lightweight operations like initialization and resource management challenging.

This paper discusses the developing market for medical robotics. It first describes some of the dynamics and market drivers in health care, and then provides an outline of the areas of consideration when developing a commercial medical robot. The paper also offers three case studies of robotic systems that have been commercialized. Finally, it summarizes some of the key ingredients to be considered for the commercialization process.

This paper presents an historic achievement. A commercial robotic surgical system was altered to enable remote surgery. This presented huge challenges because the Zeus/sup TM/ system is a tightly-coupled electromechanical system with tight sample and communication loops. We were, however, able to separate Zeus/sup TM/ into a remote surgeon-side system (located in New York City) and a patient-side system (located in Strasbourg, France). Never before have surgeons performed complete surgical tasks in the fashion presented in this paper. The remote surgical task was Laparoscopic Cholecystectomy (removal of the gall bladder) performed on animals. In this unique setup the patient (pig) was readied in the operating room in Strasbourg, France, while the operating surgeon was in Manhattan, NY. The Zeus/sup TM/ robotic system is a very safe surgical system for use in the operating room. For the remote transatlantic case, numerous safety features were built on top of those already available in Zeus/sup TM/. The ultimate goal of this development is to perform a transatlantic Lap Chole case on a human subject. As such, the animal cases were performed with the same setup, personnel, and equipment as will be used for the human case. The choices of the robotic system, networking equipment, and telecommunications lines were critical to the success of the project.

This paper presents our research at bringing the state-of-the-art in vision and robotics technologies to enhance the emerging laparoscopic surgical procedure. In particular, a framework utilizing intelligent visual modeling, recognition, and serving capabilities for assisting the surgeon in manoeuvring the scope (camera) in laparoscopy is proposed. The proposed framework integrates top-down model guidance, bottom-up image analysis, and surgeon-in-the-loop monitoring for added patient safety. For the top-down directives, high-level models are used to represent the abdominal anatomy and to encode choreographed scope movement sequences based on the surgeon's knowledge. For the bottom-up analysis, vision algorithms are designed for image analysis, modeling, and matching in a flexible, deformable environment (the abdominal cavity). For reconciling the top-down and bottom-up activities, robot serving mechanisms are realized for executing choreographed scope movements with active vision guidance.

This paper describes a practical and reliable image analysis and tracking algorithm to achieve automated instrument localization and scope manoeuvring in endoscopic surgery.

The authors present results on the performance of a 3 d.o.f. closed-chain direct-drive mechanism controlled by a high-performance real-time computer using a variety of model-based control techniques. Experimental data are used to compare the tracking performance of the computed torque control method, the resolved acceleration control method, the inverse Jacobian control method, and the individual joint PID control method over a variety of trajectories. Implementation in real-time was possible since the 3D processor robot control system was able to perform all of the required kinematic, dynamic, and control computations at a sampling rate of under 2 ms. The results presented show that the model-based methods achieved two to four times better performance than the PID control method.>

The authors discuss a concurrent programming environment and its application to a two-arm cooperative manipulation experiment on RIPS (robot instruction processing system). RIPS is a hierarchical multiprocessor architecture in which various custom and general-purpose processors are applied to a partitioning of the robot control problem. The system provides hardware support for synchronization and communication primitives, making it easier to write concurrent programs for RIPS' heterogeneous processors. The experiment demonstrated the viability of RIPS in supporting computationally intensive robot control methodologies, and as a byproduct has helped to develop a parallel programming environment for RIPS, called USE RIPS (user software environment for RIPS). By building USE RIPS on Unix and using a layered approach, it is possible to adapt or make use of various existing programs and utilities, such as the GNU and C++ compilers.>

The design and performance benchmarking of the prototype robotic instruction processing systems (RIPS) at the Center for Robotic Systems in Microelectronics at the University of California-Santa Barbara, is discussed. The architecture of RIPS is specifically geared for robot control, yet the system is general and fully programmable and does not assume any manipulator characteristics. RIPS provides sufficient computing capacity to attack important real-time sensory-based robot control problems. Compliant control, multiple manipulator coordination, and manufacturing cell-level integration are presently under study. Experimental testing in these areas is possible because of RIPS' high computational performance for robot control problems: a Stanford manipulator using the computed torque method can be controlled with an update time of 255 mu s. This time includes inverse kinematics, dynamic compensation, and proportional derivative servoing for the six-degrees-of-freedom manipulator.>

The design and simulation of RIPS, a robotic instruction processing system, are discussed. The authors are building a prototype version of RIPS which will be used as a general research tool to study problems of robot control. The architecture of RIPS is geared for robot control, yet the system is general and fully programmable and does not assume any manipulator characteristics. There is sufficient computing capacity to address any of several important automation problems such as force control, multiple manipulator coordination, or manufacturing cell-level control. Simulations show that using RIPS to control a Stanford manipulator with the computed torque method gives an update rate of 255 mu s. This simulation includes all interprocessor communication as well as the computing time necessary for equation evaluation.>

In this paper we discuss the demanding computational needs of robot control and describe a new computer architecture optimized for such problems. Inverse kinematics and dynamics for 6 degrees of freedom arms are often used as benchmarks to measure controller speed. According to current estimates, the new processor we describe can compute both of these problems, using 32 bit fixed-point operations, in less than 250 microseconds. This is an order of magnitude faster than existing state-of-the-art systems. Such benchmarks only measure a smallportion of the true robot control problem. The issues of interpolation, input/output, and multiple axis synchronization must also be addressed. As robotics becomes more advanced, the need for more compatationally intensive control algorithms (hybrid position/force control, sensory-based control, multiple robot cooperation, etc.) will grow. These now computationally-intractable problems must ultimately be computed in real-time. In this paper, we discuss current progress on a flexible (i.e. programmable) system which is fast enough to approach such problems. The system is targetted to support up to 40 synchronized axes, performing advanced control algorithms with an update rate over 1 KHz.