Scott Helmer, David Meger, Pooja Viswanathan, Sancho McCann, Matthew Dockrey, Pooyan Fazli, Tristram Southey,

Marius Muja, Michael Joya, Jim Little, David Lowe, Alan Mackworth

What is the point of robotics research?To do what humans cannot do:

What is the point of robotics research?To do tasks that humans prefer not to do:

From WALL-E

Current State in Home RoboticsOften split in a myriad of subtasks:

navigation, recognition, scene understanding, manipulation, reasoning, etc.

Boundaries and interfaces often ignored and are problematic

Systems engineering is challenging ut generally not publishable

Integrated systems are rare: eg. Stanford’s STAIR, etc.

Embodied VisionActively “seeing” for some taskHow images are acquired are not considered

traditionally in computer vision, encouraging unrealistic assumptions

Eg. Benchmark datasets in object recognitionnot representative of actual situationslearning algorithms rely on simplificationshard to evaluate whether systems work outside

lab

What is SRVC?Photo scavenger hunt, where training data is

acquired from internet

UBC’s ExperienceCurious George (2007, 2008, …)

UBC and Collaboration

Integrated our labNew research

directionsPlatform on which

to test ideasProvides quick way

to introduce new students

Designing a winner …Good design choices:

Eye level camera on PTUPeripheral / foveal system with high res. camera

Good Algorithms:SLAM navigationSaliency and visual coverage SIFT based recognitionCategory recognition

After initial phase, can now focus more on research

What does the SRVC do well?Compelling taskVisibility

AAAI 2007, Vancouver, CanadaCVPR 2008, Anchorage, USAISVC 2009, Las Vegas, USA

Responsive to entrantsEncourages open sourceEvolvesInteresting for audience

Future Directions for SRVCAttract more competitors

more synthesisgreater exposuremore exciting

Improve research outcomesResearch competitions should advance

research rather than simply display current technology

Should reflect successful research, not engineering that doesn’t transfer

Attracting CompetitorsCurrently:

2 leagues, Software league and Robot leagueSoftware league is too similar to competitions

like PASCAL VOCRobot league poses challenges due to shipping,

unknown environment, etc.

Software LeagueOffer more sensory modalities

Stereo vision, high res images, videoOffer mapping info, camera poseLarger test sets for more statistical validityImprove research outcomes (later)

Robot LeagueProvide more detailed specifications for

contest environmentProvide standardized robot platform and

architecture (like ROS)+ Avoids per team risk of shipping/unknowns+ Provides more opportunities for code sharing- Also involves numerous challenges

Focus on more interesting challenges like viewpoint planning

Improving Research Outcomes

Improving Research OutcomesImprove realism – more clutter, occlusions, no

white tablecloths etc.Make context relevantAllow access to pre-built datasets and priors

Web data is generally not suited for 3D recognition

Forefront of vision research requires richer datasets

Greater variety of objects and situationsPoints for

ConclusionCompetitions can provide an evolving setting

in which to evaluate current technologiesSRVC frames a challenging problem for

embodied vision, which is difficult to evaluate using benchmarks

Numerous changes can be made to attract more competitors and improve research outcomes