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.

New in 2007 we have mounted phototransistors on the car-based platform for use in designing and testing boundary tracking algorithms with noisy data. Preliminary results show that a recently developed algorithm (see paper by Jin and Bertozzi) is effective in boundary tracking in noisy environments.