Demo Data from SIGIR 2026 / reviewers in the wild / expert
Terry Kientz
dblp:81/3177
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2Systems, architecture and hardware · 2Applied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
1 paper |
Human-robot interaction · 67% Interaction techniques and input · 33% | |
| Artificial intelligence
1 paper |
Motion planning and robot control · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-robot interaction
assistive robotics |
0.0 | 1 | 2002 | Human Robot Interaction: Application to Smart Wheelchairs · ICRA 2002 |
Interaction techniques and input › sensor-based interaction
camera-based interaction |
0.0 | 1 | 2002 | Human Robot Interaction: Application to Smart Wheelchairs · ICRA 2002 |
Human-robot interaction › assistive robotics
smart wheelchair |
0.0 | 1 | 2002 | Human Robot Interaction: Application to Smart Wheelchairs · ICRA 2002 |
Methods — techniques the papers use, named apart from their topics
vision-based interface · 0.1sensor suite · 0.1control algorithm · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Variable topology truss: Design and analysisabstractThis paper introduces a new class of self-reconfigurable robot: the variable topology truss (VTT). Related to an existing class of robots, the variable geometry truss (VGT), variable topology trusses have the additional capability to change the topology of the truss through self-reconfiguration. The hardware necessary to achieve this is introduced, and the constraints and capabilities of this new type of robot are analyzed by introducing the concept of a topology neighbor graph. Lastly, the minimal reconfigurable VTTs, which require 18 members, are identified and their achievable topologies are enumerated. Alexander Spinos, Devin Carroll, Terry Kientz, Mark Yim |
IROS | 3 |
| 2017 | Automated System for Semantic Object Labeling With Soft-Object Recognition and Dynamic Programming SegmentationabstractThis paper presents an automated robotic system for generating semantic maps of inventory in retail environments. In retail settings, semantic maps are labeled maps of stores where each discrete section of shelving is assigned a department label describing the types of products on that shelf. Starting from a metric map of the store, the robot autonomously extracts the shelf boundaries, generates a distance-optimal tour of the store to view every shelf, and follows the tour while avoiding unmapped clutter and moving people. The robot creates a point cloud of the store using the data collected from this tour. We introduce a novel soft-object assignment algorithm to create a virtual map and a dynamic programming algorithm to segment this map. These algorithms use a priori information about the products to boost data from laser and camera sensors in order to recognize and semantically label objects. The primary contribution of this paper is the integration of multiple systems for automated path planning, navigation, object recognition, and semantic mapping. This paper represents an important contribution toward deploying mobile robots in dynamic human environments. Jonas Cleveland, Dinesh Thakur, Philip M. Dames, Cody J. Phillips 0001, Terry Kientz, Kostas Daniilidis, John Bergstrom, Vijay Kumar 0001 |
IEEE Trans Autom. Sci. Eng. | 5 |
| 2002 | Human Robot Interaction: Application to Smart WheelchairsabstractAddresses the problem of human robot interaction with application to the design of assistive devices. We describe the design and development of a prototype of a smart wheelchair that can be commanded by a rider. Specifically, we focus on (a) the vision-based human interaction interface; (b) the suite of sensors on the chair, and (c) the software architecture and the control algorithms used to control the chair. R. S. Rao, K. Conn, Sang-Hack Jung, Jayantha Katupitiya, Terry Kientz, Vijay Kumar 0001, James P. Ostrowski, Sarangi Patel, Camillo J. Taylor |
ICRA | 5 |