Robotic Testbed
Inspiration: during summer 2004, we went to CalTech where we used
Richard Murray's
Multi-vehicle wireless testbed ,
which includes the fully autonomous Kelly vehicle shown to the right.
That vehicle has an onboard laptop computer, two ducted fans for self-propulsion, and it wears a hat with a bar code on top that is read by an overhead vision
tracking system. Information from the vision system is fed back to the vehicle
through wireless networking. Many Kellys can communicate on the floor
of the testbed through this network.
The MVWT platform inspired us to build our own platform at UCLA. Below
we describe our first generation testbed.
First generation testbed:
Kevin Leung, Chung Hsieh, and Rick Huang built the vehicles platform.
Our testbed arena is a 5X8 area; requiring much smaller vehicles
than the CalTech Kellys. We have developed a system using radio controlled
cars. The algorithms are programmed off-board and controls are
sent to the individual cars using different radio frequencies.
We have an overhead vision tracking system modelled on the one
at CalTech.
Here is a schematic of the vehicles platform.
On left is a photo of the group and the first generation of vehicles.
Left to right - Maria D'Orsogna, Chung Hsieh, Kevin Leung, Yao-Li Chuang, and Rick Huang. On the right is a close up photo of the first generation
of vehicles.
Here is a videoclip of a demo involving area servicing by three vehicles.
In the video, a student uses a stick to flash target images to the overhead cameras. One of the vehicles must then visit that target site.
Otherwise the vehicles maintain a holding pattern.
A second generation of the testbed was build in summer 2006.
The original vehicle is improved with on-board range sensing,
on-board computing, and wireless communication, while
maintaining economic feasibility and scale. A second, tank-based
platform, uses a flexible caterpillar-belt drive and the same
modular sensing and communication components.
We demonstrate practical use of the testbed for algorithm validation by
implementing a recently proposed cooperative steering law
involving obstabcle avoidance.
The tank-based vehicle proves to be quite useful in the implementation
of an environmental mapping algorithm based on ENO interpolation.
In 2007 we mounted phototransistors on the car-based platform (shown left)
for use in designing and testing boundary tracking algorithms
with noisy data. Our testbed results show that a recently
developed algorithm (see paper by Jin and Bertozzi) is
effective in boundary tracking in noisy environments.
Experimental work on boundary tracking was published in the 2009 American Control Conference. See publication list for
these and other papers.
