In 1971, anthropologist Robert Trivers published a landmark article titled "The Evolution of Reciprocal Altruism". Trivers argues that an altruistic action from one organism to a second organism will be detrimental to the ¯rst organism but will benefit the second organism. However, over the long term, the second organism can reciprocate the act, resulting in long term benefits for both.

Accordingly, we propose the hypothesis that within the context of Multi-Robot Communities (MRC), reciprocal altruism is key to optimizing individual robot fitness functions over long time horizons. Unlike typical Multi-Robot Systems (MRS) in which robots cooperate to maximize global fitness functions, MRC are comprised of individual robots that have independent goals. While it may be beneficial for robots to act selfishly in the short term, robots may gain more benefits over the long term by exhibiting altruistic behavior.

Currently, we plant to explore the application of this social model to communities of multiple Unmanned Aerial Vehicles (UAVs) and Autonomous Underwater Vehicles (AUVs). We hope to design methods to estimate and control altruistic actions between AUVs/UAVs such that altruistic relationships between vehicles can grow over time, while protecting vehicles against selfish vehicles. This design includes analysis of the evolutionary properties of the altruistic relationships through standard system stability analysis.

Fish Tracking via Underwater Robots

This project builds from previous work on tracking large mouth bass in Ontario, Canada. In our current project, we are working with Biologist Pat Fidopiastis on tracking the shallow water tropical squid Euprymna scolopes. Over the last two decades, this specides of squid has emerged as a premier model for studying mechanisms of bacterial host-colonization. In order to discover the cryptic role of luminescence, the PI and Cal Poly Biologist Dr. Pat Fidopiastis plan to track and observe the squid within its own environment. Unlike previous lab studies, researchers hope to draw correlations between behaviors (bioluminescence, hunting, mating, etc.) and variables associated with the squids habitat. Squid tracking will be accomplished through a VideoRay ROV equipped with a video camera, a scanning sonar based localization system, and a vision based squid tracking software. The expedition is scheduled for the summer of 2009. This project is funded through Cal Poly's ONR C3RP Grant.

Ocean Modelling with AUVs

Funded through the Cal Poly ONR C3RP grant, this one year project involves the use of AUVs to reduce models in an ocean modeling system. The system will run a fine-scale (100-500m level) resolution dynamic model that estimates ocean model properties (e.g. temperature). Mathematician Paul Choboter and Biologist Mark Moline will setup the ocean model on one of Cal Poly's computer clusters. The model will integrate measurements from a variety of remote sensors. The PI's contribution to the work will be developing a planner that constructs AUV paths to gain measurements which are optimal in terms of model error reduction. This project will provide a path planner for the Iver2 that can be queried to construct bids within the framework for altruism.

Coordination and Control of Multi-Robot Systems

Many mobile robot applications, such as autonomous mining, planetary exploration, and surveillance systems can benefit from the use of multiple robots working cooperatively in a common environment. Creating collision-free plans for the motion of a large number of robots working together is a challenging task.

In the past we took probabilistic road map approaches. Recently, we have developed a multi-phase approach to efficiently solve this planning problem.

Intelligent Vehicles

The idea of autonomous road vehicles sharing traffic and road condition information has significant potentials in improving road safety . The goal of this project is to devise a method to intelligently filter external  information exchanged between vehicles in highly dynamic road and computer networks, in addition with information from a vehicle's own sensors.  However, from a practical standpoint it is desirable to minimize the number and complexity of sensors implemented on each vehicle to improve the feasibility of applying such technology in the real world. The vehicle network not only allows a vehicle to have a perception of the environment in close proximity but also of events and conditions in downstream traffic which can considerably improve driver awareness.

Autonomous Outdoor Navigation

Applying concepts of mobile robotics from the laboratory to an outdoor vehicle introduces many new challenges. The vehicle must now localize itself in a large and almost structure-less environment. A greater amount of uncertainty is introduced in motion control due to changes in elevation and terrain. The goal of this project is to convert an amphibious vehicle into an autonomous machine capable of navigating from defined starting and goal positions. This vehicle will then serve as a platform for future research.

Autonomous Underwater Robots

Underwater robots have traditionally been limited to oceanic research due to their large size and high cost. However, with today's level of personal computing power, intelligent robotics have becomes accessible to a broad range of people and applications.

Modular and Reconfigurable Robots

Modular and Reconfigurable Robot (MRR) manipulators can add flexibility to a manufacturing setting where changes in the manufacturing system configuration are common. This project focuses on control of MRRs as well as configuration optimization.