Research Projects
Automated Transport and Retrieval System (ATRS)
The Automatic Transport and Retrieval System (ATRS) is being developed by Freedom Sciences, LLC in conjunction with Lehigh University and Carnegie Mellon. By employing robotics and automation technologies, the core of ATRS - the "smart" wheelchair system will autonomously navigate between the driver's position and a powered lift at the rear of the vehicle.This enabling technology will allow physically challenged operators to travel independently using a standard passenger vehicle that fully conforms to NHTSA safety requirements. Furthmore, unlike alternate approaches the vehicle integration is minimally invasive, and will not affect resale value.
Our work on the ATRS program focuses on the algorithms for wheelchair position estimation and control for reliable and autonomously docking and undocking the wheelchair onto the lift platform. During the last three years, we have developed both a proof of concept system which employs a vision-based localization scheme, and the current Beta system which employs a LIDAR for estimating the wheelchair position. And the current Beta system will be improved to be 100% reliability and planed market launch in Sep 2007.
The DARPA Urban Challenge
Lehigh University, the University of Pennsylvania and ATL @ Lockheed Martin have joined forces to form the Ben Franklin Racing Team, whose objective is to develop safe autonomous vehicles for urban navigation. The team is fielding an entry in the DARPA Urban Grand Challenge with Lehigh's efforts being spear-headed by our group in the VADER Lab. In this competition, autonomous vehicles must traverse a 60-mile urban course while obeying traffic laws and coping with both stationary obstacles as well as other moving traffic. Our primary vehicle is a modified hybrid Toyota Prius named Little Ben. Our focus will largely be in perception using LIDARs and stereo vision systems for road/lane segementation and obstacle detection.
Optimization Techniques for Planning and Estimation in Multi-agent Systems
We are interested in developing computationally efficient algorithms for planning and estimation, with applications to robot teams and wireless sensor networks. This work leverages recent advances in convex optimization. We attempt to extend these by establishing application specific complexity bounds and investigating distributed implementations. Topics of interest include motion planning, multi-robot localization, and target tracking.
In recent work, we investigated techniques for optimal shape changes in robot teams. Our definition of optimality is defined as either minimizing the total distance that the robots must travel or the minimizing the maximum distance that any team member must travel. Using second-order programming (SOCP) techniques, we derived optimal solutions in both SE(2) and R3. The latter also allows for complete regulation of scale.
Pennsylvania Assistive Technology Commercialization Initiative (PATCI)
PATCI is a pilot program funded through the Technology Collaborative (TTC) to encourage innovation and commercialization of Assistive Technology (AT) and Quality of Life Technology (QoLT) products. This program provides seed funding grants of up to $5,000 to student teams working on projects in AT/QoLT. Funding will be provided to student projects with commercialization potential, and which build upon technologies within s focus areas of electronics, computers, networking, and robotics. Student projects that are successful at this Phase-1 stage will be eligible to compete for Phase-2 commercialization grants of up to $30,000.
Funded student PATCI Projects include:
- RFID Systems for Loss Prevention in Assistive Living Facilities
Hybrid Free-space Optics/Radio Frequency (FSO/RF) Networks for Mobile Robot Teams
Consider a scenario where the infrastructure of a metropolitan area network (MAN) is incapacitated by a man-made or natural disaster (e.g., an earthquake). MAN connectivity could be automatically restored by a team of autonomous mobile agents if each were equipped with a communications medium capable of patching the broken links. However, in this case the link distance and throughput requirements might be of such magnitude to render radio frequency (RF) based approaches ineffective.
We predict that such throughput intensive scenarios will lead to the emergence of hybrid FSO/RF based mobile ad-hoc network (MANET) architectures. The benefits of such a model are obvious. An FSO link in any network provides a high throughput channel over which time sensitive data can be transmitted. Many commercially available FSO devices already provide throughput rates in the Gbps range. Additionally, FSO provides constant throughput over a much longer range than RF-based channels.
