Robotic lighter-than-air vehicles, or aerobots, are strategic surveying and instrument deployment platforms for the exploration of planets and moons with an atmosphere, such as Venus, Mars and Titan. Aerobots are characterized by modest power requirements, extended mission duration and long traverse capabilities, and the ability to transport and deploy scientific instruments and in-situ laboratory facilities over vast distances. With the arrival of the Huygens probe at Saturn's moon Titan in early 2005, there is considerable interest in a follow-on mission that would use a substantially autonomous aerobot to explore Titan's surface. In this paper, we discuss first steps towards the development of an autonomy architecture and a core set of perception, reasoning and control technologies for a future Titan aerobot. We provide an overview of the autonomy architecture, which integrates perception-based flight planning and control, vehicle health monitoring and safing, long-range mission planning and monitoring, and vision-based science site surveying. We describe the JPL aerobot and the onboard avionics architecture testbeds, and conclude with results from initial teleoperated test flights.

Tracked mobile robots in the 20 kg size class are under development for applications in urban reconnaissance. For efficient deployment, it is desirable for teams of robots to be able to automatically execute path following behaviors, with one or more followers tracking the path taken by a leader. The key challenges to enabling such a capability are (1) to develop sensor packages for such small robots that can accurately determine the path of the leader and (2) to develop path following algorithms for the subsequent robots. To date, we have integrated gyros, accelerometers, compass/inclinometers, odometry, and differential GPS into an effective sensing package. The paper describes the sensor package, sensor processing algorithm and path tracking algorithm we have developed for the leader/follower problem in small robots and shows the results of performance characterization of the system. We also document pragmatic lessons learned about design, construction, and electromagnetic interference issues particular to the performance of state sensors on small robots.