In this paper, the iterative learning control (ILC) literature published between 1998 and 2004 is categorized and discussed, extending the earlier reviews presented by two of the authors. The papers includes a general introduction to ILC and a technical description of the methodology. The selected results are reviewed, and the ILC literature is categorized into subcategories within the broader division of application-focused and theory-focused results.

Iterative Learning Control: Brief Survey and Categorization

This paper presents the complete development and analysis of a soft robotic platform that exhibits peristaltic locomotion. The design principle is based on the antagonistic arrangement of circular and longitudinal muscle groups of Oligochaetes. Sequential antagonistic motion is achieved in a flexible braided mesh-tube structure using a nickel titanium (NiTi) coil actuators wrapped in a spiral pattern around the circumference. An enhanced theoretical model of the NiTi coil spring describes the combination of martensite deformation and spring elasticity as a function of geometry. A numerical model of the mesh structures reveals how peristaltic actuation induces robust locomotion and details the deformation by the contraction of circumferential NiTi actuators. Several peristaltic locomotion modes are modeled, tested, and compared on the basis of speed. Utilizing additional NiTi coils placed longitudinally, steering capabilities are incorporated. Proprioceptive potentiometers sense segment contraction, which enables the development of closed-loop controllers. Several appropriate control algorithms are designed and experimentally compared based on locomotion speed and energy consumption. The entire mechanical structure is made of flexible mesh materials and can withstand significant external impact during operation. This approach allows a completely soft robotic platform by employing a flexible control unit and energy sources.

Meshworm: A Peristaltic Soft Robot With Antagonistic Nickel Titanium Coil Actuators

http://foresight.ifmo.ru/ict/shared/files/201311/1_123.pdf

Decentralized control: An overview

This paper describes the Robotarium — a remotely accessible, multi-robot research facility. The impetus behind the Robotarium is that multi-robot testbeds constitute an integral and essential part of the multi-robot research cycle, yet they are expensive, complex, and time-consuming to develop, operate, and maintain. These resource constraints, in turn, limit access for large groups of researchers and students, which is what the Robotarium is remedying by providing users with remote access to a state-of-the-art multi-robot test facility. This paper details the design and operation of the Robotarium and discusses the considerations one must take when making complex hardware remotely accessible. In particular, safety must be built into the system already at the design phase without overly constraining what coordinated control programs users can upload and execute, which calls for minimally invasive safety routines with provable performance guarantees.

/pdf/the-robotarium-a-remotely-accessible-swarm-robotics-research-jfnikj6svh.pdf

The Robotarium: A remotely accessible swarm robotics research testbed

In the future, robotic surgical assistants may assist surgeons by performing specific subtasks such as retraction and suturing to reduce surgeon tedium and reduce the duration of some operations We propose an apprenticeship learning approach that has potential to allow robotic surgical assistants to autonomously execute specific trajectories with superhuman performance in terms of speed and smoothness In the first step, we record a set of trajectories using human-guided backdriven motions of the robot These are then analyzed to extract a smooth reference trajectory, which we execute at gradually increasing speeds using a variant of iterative learning control We evaluate this approach on two representative tasks using the Berkeley Surgical Robots: a figure eight trajectory and a two handed knot-tie, a tedious suturing sub-task required in many surgical procedures Results suggest that the approach enables (i) rapid learning of trajectories, (ii) smoother trajectories than the human-guided trajectories, and (iii) trajectories that are 7 to 10 times faster than the best human-guided trajectories

/pdf/superhuman-performance-of-surgical-tasks-by-robots-using-2b7ow3oky4.pdf

Superhuman performance of surgical tasks by robots using iterative learning from human-guided demonstrations

96 A Survey of Iterative Learning Control Al earning-based method for high-performance tracking control

This paper presents an overview of the hovercraft testbed for decentralized control (HoTDeC) testbed at the University of Illinois. It describes the architecture of the system and its subsystems and provides details about modeling tine system and the control dynamics of the hovercraft vehicles. The project focuses on implementing distributed strategies for coordinated maneuvers and investigating approaches for dealing systematically with network latency as well as the application of higher level control algorithms.

Derek King

Papers

96 A Survey of Iterative Learning Control Al earning-based method for high-performance tracking control

Multivehicle systems control over networks: a hovercraft testbed for networked and decentralized control

Multivehicle Systems Control over Networks