Ian Walker, Clemson University
This talk will provide an overview of research in biologically inspired continuous backbone “trunk and tentacle” continuum robots. In particular, robots inspired by octopus arms and plants (vines) will be discussed. Use of these robots for novel inspection and manipulation operations, targeted towards Aging in Place applications and Space-based operations, will be discussed.Ian Walker received the B.Sc. in Mathematics from the University of Hull, England, in 1983 and the M.S. and Ph.D. in Electrical and Computer Engineering from the University of Texas at Austin in 1985 and 1989. He is a Professor in the Department of Electrical and Computer Engineering at Clemson University. Professor Walker’s research focuses on research in the construction, modeling, and application of continuum robots.
Round-table discussion of current topics in robotics with faculty and students. Coffee and cookies are served.
The liquid phase processing of polymers has been used in the last 100 years to produce items that vary in size and function from buoyant boat hulls to the living hinges on tic-tac boxes. Recently, the fields of stretchable electronics and soft robotics have made significant progress in manufacturing approaches to add increased mechanical function as well as sensory feedback from the additive manufacturing of soft materials, including polymers and elastomers. This talk will be a survey of the work my research group, the Organic Robotics Laboratory, has contributed in this space. Much of the work will revolved around a 3D printing process called Projection Stereolithography. Our group leases a Carbon M1 3D printer that is available for other researchers to use, so attending this talk can also be seen as an introduction to the process and its capabilities.
Getting a robot to perform a complex task, for example completing the DARPA Robotics Challenge, typically requires a team of engineers who program the robot in a time consuming and error prone process and who validate the resulting robot behavior through testing in different environments. The vision of synthesis for robotics is to bypass the manual programming and testing cycle by enabling users to provide specifications – what the robot should do – and automatically generating, from the specification, robot control that provides guarantees for the robot’s behavior.
In this talk I will describe the work done in my group towards realizing the synthesis vision. I will discuss what it means to provide guarantees for physical robots, types of feedback we can generate, specification formalisms that we use and our approach to synthesis for different robotic systems such as modular robots, soft robots and multi robot systems.
Competence in pedestrian social navigation requires a robot to exhibit many strengths, from perceiving the intentions of others through social signals to acting clearly to convey intent. It is made more difficult by the presence of many individual people with their own agendas as well as by the fact that all communication and coordination occurs implicitly through social signaling (chiefly gross body motion, eye gaze, and body language). Furthermore, much of the information people glean about one another’s intentions is derived from the social context. For example, office workers are more likely to be heading towards the cafeteria if it is lunchtime and towards the exit if it is time to go home.
In this talk, I explore some of the mathematical tools that allow us to tease apart the problem of social navigation into patterns that distill enough of the complexity to be learnable. One of the key problems is to predict the future motions of others based on an observed “path prefix”. Past results have shown that geometric prediction of pedestrian motion is nearly impossible to do accurately due to the very fact that people are behaving in a socially competent manner, since they react to other people in ways that achieve their joint goals. Instead, I show how trajectories of navigating pedestrians can be jointly predicted topologically. This prediction can readily be learned in order to understand how people intend to avoid colliding with one another while achieving their goals.
When viewed from the rear a bicycle looks like an inverted pendulum. Where the wheels touch the ground, it has an effective hinge point. So, if a bike tips a little, gravity acting on the center of mass tends to tip it more. So, superficially, a bike is unstable. Yet in practice, moving bicycles don’t fall over. Why not? This question has three variants. How do bike riders control control bikes to stay up? That is, what forces are invoked to keep the bike from falling? Second, how do people balance bikes when riding no hands? And third, how does ghost riding work? That is, at least some bikes won’t fall over when they are moving fast enough, even with no rider. How does that happen?
The third question, about ghost riding (bicycle self stability), being purely a question of mechanics, seems simplest. In the folk lore, there are two dominant theories: the gyroscopic theory of Klein and Sommerfeld (~1911) and the Castor (aka ‘trail’) theory of Jones (1970). By means of examples, we now know that both were wrong. Gyroscopic terms and ‘positive’ castor are neither necessary nor sufficient, separately or in combination, for bicycle self-stability.
As for what riders do, hands on or hands off, the centrifugal theory of bicycle balance is pretty complete: when having an undesirable fall to the right, you should steer to the right.
Sue Fussell, Malte Jung, Guy Hoffman, Ross Knepper
Several faculty who study human-robot interaction present some of the best practices in HRI research. HRI differs from many other subfields of robotics because it deals with humans. We are limited both in our understanding of human psychology and in our ability to experiment on humans. To help audiences better appreciate HRI research presentations, this talk and discussion will cover popular approaches to conducting HRI research, including experimental methodology and useful metrics for evaluation of experiments.
Hosted by Guy Hoffman
We will present lightning talks of human-robot-interaction themed papers that have been submitted this year to conferences such as HRI, CHI, and AAAI. Talks will be max 5 minutes and preferably presented by the student author.
Every day, Amazon picks, packs, and ships millions of customer orders from a network of fulfillment centers (FCs) spread all over the globe. With each FC holding millions of inventory items, most customer orders requiring a unique combination of several of these items, and many orders needing to be shipped within a few hours of being placed, cutting-edge advances in technology are needed to ensure that orders are fulfilled efficiently and shipped on time. In this talk, we will present Amazon’s mobile robotic fulfillment solution, consisting of a fleet of thousands of drive units per FC that deliver inventory shelves to picking associates. We will describe the solution’s key advantages and its main components, and provide an overview of the complex resource allocation and planning problems addressed by its sophisticated algorithms. We will also discuss the Amazon Robotics Challenge for advancing the state of the art in item manipulation and grasping, as well as a couple of big open problems in robotic warehousing.
In this talk I will present an Elastomeric Passive Transmission (EPT) which increases the maximum output force and actuation speed of tendon-driven actuators. The EPT achieves these improvements with minimal impact to the size, weight, or cost of the system. Using inherent tendon tension to strain elastomeric struts toward the center of the motor-mounted spool, the EPT passively adjusts the effective gearing ratio of a motor. This allows a tendon-driven actuator to move with high speed when unimpeded, and with high-force under load. Our EPTs can be used with low-cost motors to achieve the performance (maximum force and speed) of a high-cost motor at a drastically reduced cost, or they can further improve the performance of higher quality, more expensive motors. To demonstrate the utility of these EPTs, we have integrated them into a prosthetic hand which meets, and in some cases exceeds, the performance of a high-end commercial prosthetic with motors that are 10% the cost. Our prosthetic hand has 6 active degrees of freedom which drive 5 3D-printed, soft digits (one for the flexion of each finger, and two for the thumb). Each finger can fully close in < .6 seconds and can grasp with a maximum force of ~40N. The entire hand has a mass of ~400 grams and a material cost of < $500.