Charles F. Bergh

Algorithms and sensors for small robot path following

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.

Mobile Manipulation and Mobility as Manipulation-Design and Algorithms of RoboSimian

This article presents the hardware design and software algorithms of RoboSimian, a statically stable quadrupedal robot capable of both dexterous manipulation and versatile mobility in difficult terrain. The robot has generalized limbs and hands capable of mobility and manipulation, along with almost fully hemispherical three-dimensional sensing with passive stereo cameras. The system is semiautonomous, enabling low-bandwidth, high latency control operated from a standard laptop. Because limbs are used for mobility and manipulation, a single unified mobile manipulation planner is used to generate autonomous behaviors, including walking, sitting, climbing, grasping, and manipulating. The remote operator interface is optimized to designate, parametrize, sequence, and preview behaviors, which are then executed by the robot. RoboSimian placed fifth in the DARPA Robotics Challenge Trials, demonstrating its ability to perform disaster recovery tasks in degraded human environments.

Passive perception system for day/night autonomous off-road navigation

Passive perception of terrain features is a vital requirement for military related unmanned autonomous vehicle operations, especially under electromagnetic signature management conditions. As a member of Team Raptor, the Jet Propulsion Laboratory developed a self-contained passive perception system under the DARPA funded PerceptOR program. An environmentally protected forward-looking sensor head was designed and fabricated in-house to straddle an off-the-shelf pan-tilt unit. The sensor head contained three color cameras for multi-baseline daytime stereo ranging, a pair of cooled mid-wave infrared cameras for nighttime stereo ranging, and supporting electronics to synchronize captured imagery. Narrow-baseline stereo provided improved range data density in cluttered terrain, while wide-baseline stereo provided more accurate ranging for operation at higher speeds in relatively open areas. The passive perception system processed stereo images and outputted over a local area network terrain maps containing elevation, terrain type, and detected hazards. A novel software architecture was designed and implemented to distribute the data processing on a 533MHz quad 7410 PowerPC single board computer under the VxWorks real-time operating system. This architecture, which is general enough to operate on N processors, has been subsequently tested on Pentium-based processors under Windows and Linux, and a Sparc based-processor under Unix. The passive perception system was operated during FY04 PerceptOR program evaluations at Fort A. P. Hill, Virginia, and Yuma Proving Ground, Arizona. This paper discusses the Team Raptor passive perception system hardware and software design, implementation, and performance, and describes a road map to faster and improved passive perception.

Towards a substantially autonomous aerobot for exploration of Titan

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 Saturns moon Titan in early 2005, there is considerable interest in a follow-on mission that would use a substantially autonomous aerobot to explore Titans 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.

Sensors and algorithms for small robot leader/follower behavior

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 leader/follower behaviors, with one or more followers tracking the pat+6|+ken 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 for a small urban robot. This 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.

Flight Testing of Terrain-Relative Navigation and Large-Divert Guidance on a VTVL Rocket

Since 2011, the Autonomous Descent and Ascent Powered-Flight Testbed (ADAPT) has been used to demonstrate advanced descent and landing technologies onboard the Masten Space Systems (MSS) Xombie vertical-takeoff, vertical-landing suborbital rocket. The current instantiation of ADAPT is a stand-alone payload comprising sensing and avionics for terrain-relative navigation and fuel-optimal onboard planning of large divert trajectories, thus providing complete pin-point landing capabilities needed for planetary landers. To this end, ADAPT combines two technologies developed at JPL, the Lander Vision System (LVS), and the Guidance for Fuel Optimal Large Diverts (G-FOLD) software. This paper describes the integration and testing of LVS and G-FOLD in the ADAPT payload, culminating in two successful free flight demonstrations on the Xombie vehicle conducted in December 2014.

Autonomous Flight Control for a Planetary Exploration Aerobot

Robotic lighter-than-air vehicles, or aerobots, provide a strategic platform for the exploration of planets and moons with an atmosphere, such as Venus, Mars, Titan and the gas giants.