Brian Mayton

An Electric Field Pretouch system for grasping and co-manipulation

Pretouch sensing is longer range than contact, but shorter range than vision. The hypothesis motivating this work is that closed loop feedback based on short range but non-contact measurements can improve the reliability of manipulation. This paper presents a grasping system that is guided at short range by Electric Field (EF) Pretouch. We describe two sets of experiments. The first set of experiments involves human-to-robot and robot-to-human handoff, including the use of EF Pretouch to detect whether or not a human is also touching an object that the robot is holding, which we call the “co-manipulation state.” In the second set of experiments, the robot picks up standalone objects. We describe a number of techniques that servo the arm and fingers in order to both collect relevant geometrical information, and to actually perform the manipulation task.

Gambit: An autonomous chess-playing robotic system

This paper presents Gambit, a custom, mid-cost 6-DoF robot manipulator system that can play physical board games against human opponents in non-idealized environments. Historically, unconstrained robotic manipulation in board games has often proven to be more challenging than the underlying game reasoning, making it an ideal testbed for small-scale manipulation. The Gambit system includes a low-cost Kinect-style visual sensor, a custom manipulator, and state-of-the-art learning algorithms for automatic detection and recognition of the board and objects on it. As a use-case, we describe playing chess quickly and accurately with arbitrary, uninstrumented boards and pieces, demonstrating that Gambits engineering and design represent a new state-of-the-art in fast, robust tabletop manipulation.

DoppelLab: Tools for exploring and harnessing multimodal sensor network data

We present DoppelLab, an immersive sensor data browser built on a 3-d game engine. DoppelLab unifies independent sensor networks and data sources within the spatial framework of a building. Animated visualizations and sonifications serve as representations of real-time data within the virtual space.

Robot, feed thyself: Plugging in to unmodified electrical outlets by sensing emitted AC electric fields

We describe a robot that is able to autonomously plug itself in to standard, unmodified electrical outlets by sensing the 60Hz electric fields emitted from the outlet. The building electrical infrastructure is not modified in any way. Unlike previous powerline localization work, no additional signal is injected in the powerlines—the already present AC power carrier signal in the outlet is used as the localization beacon. This technique is faster, more accurate, and potentially less expensive than previously reported vision-based systems for autonomous plugging in.

TRUSS: Tracking Risk with Ubiquitous Smart Sensing

We present TRUSS, or Tracking Risk with Ubiquitous Smart Sensing, a novel system that infers and renders safety context on construction sites by fusing data from wearable devices, distributed sensing infrastructure, and video. Wearables stream real-time levels of dangerous gases, dust, noise, light quality, altitude, and motion to base stations that synchronize the mobile devices, monitor the environment, and capture video. At the same time, low-power video collection and processing nodes track the workers as they move through the view of the cameras, identifying the tracks using information from the sensors. These processes together connect the context-mining wearable sensors to the video; information derived from the sensor data is used to highlight salient elements in the video stream. The augmented stream in turn provides users with better understanding of real-time risks, and supports informed decision-making. We tested our system in an initial deployment on an active construction site.

WristQue: A personal sensor wristband

WristQue combines environmental and inertial sensing with precise indoor localization into a wristband wearable device that serves as the users personal control interface to networked infrastructure. WristQue enables users to take control of devices around them by pointing to select and gesturing to control. At the same time, it uniquely identifies and locates users to deliver personalized automatic control of the users environment. In this paper, the hardware and software components of the WristQue system are introduced, and a number of applications for lighting and HVAC control are presented, using pointing and gesturing as a new human interface to these networked systems.