Michael McHenry

CLARAty: Challenges and Steps toward Reusable Robotic Software

We present in detail some of the challenges in developing reusable robotic software. We base that on our experience in developing the CLARAty robotics software, which is a generic object-oriented framework used for the integration of new algorithms in the areas of motion control, vision, manipulation, locomotion, navigation, localization, planning and execution. CLARAty was adapted to a number of heterogeneous robots with different mechanisms and hardware control architectures. In this paper, we also describe how we addressed some of these challenges in the development of the CLARAty software.

Multi-sensor, high speed autonomous stair climbing

Small, tracked mobile robots designed for general urban mobility have been developed for the purpose of reconnaissance and/or search and rescue missions in buildings and cities. Autonomous stair climbing is a significant capability required for many of these missions. In this paper we present the design and implementation of a new set of estimation and control algorithms that increase the speed and effectiveness of stair climbing. We have developed: (1) a Kalman filter that fuses visual/laser data with inertial measurements and provides attitude estimates of improved accuracy at a high rate; and (2) a physics based controller that minimizes the heading error and maximizes the effective velocity of the vehicle during stair climbing. Experimental results using a tracked vehicle validate the improved performance of this control and estimation scheme over previous approaches.

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.

Guidance, Navigation, and Control Technology Assessment for Future Planetary Science Missions

Future planetary explorations envisioned by the National Research Councils (NRCs) report titled Vision and Voyages for Planetary Science in the Decade 2013-2022, developed for NASA Science Mission Directorate (SMD) Planetary Science Division (PSD), seek to reach targets of broad scientific interest across the solar system. This goal requires new capabilities such as innovative interplanetary trajectories, precision landing, operation in close proximity to targets, precision pointing, multiple collaborating spacecraft, multiple target tours, and advanced robotic surface exploration. Advancements in Guidance, Navigation, and Control (GN&C) and Mission Design in the areas of software, algorithm development and sensors will be necessary to accomplish these future missions. This paper summarizes the key GN&C and mission design capabilities and technologies needed for future missions pursuing SMD PSDs scientific goals.

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.

Vision-based localization in urban environments

As part of DARPAs MARS2020 program, the Jet Propulsion Laboratory has developed a vision-based system for localization in urban environments that requires neither GPS nor active sensors. System hardware consists of a pair of small FireWire cameras and a standard Pentium-based computer. The inputs to the software system consist of: 1) a crude grid-based map describing the positions of buildings, 2) an initial estimate of robot location and 3) the video streams produced by the stereo pair. At each step during the traverse the system: captures new image data, finds image features hypothesized to lie on the outside of a building, computes the range to those features, determines an estimate of the robots motion since the previous step and combines that data with the map to update a probabilistic representation of the robots location. This probabilistic representation allows the system to simultaneously represent multiple possible locations. For our testing, we have derived the a priori map manually using non-orthorectified overhead imagery, although this process could be automated. The software system consists of three primary components. The first is a stereo-based visual odometry system that calculates the 6-degree of freedom camera motion between sequential frames. The second component uses a set of heuristics to identify straight-line segments that are likely to be part of a building exterior. Ranging to these straight-line features is computed using binocular or wide-baseline stereo. The resulting features and the associated range measurements are fed to the third software component, a particle-filter based localization system. This system uses the map and the most recent results from the first two to update the estimate of the robots location. This report summarizes the design of both the hardware and software and describes the results of applying the system to the global localization of a camera system over an approximately half-kilometer traverse across JPLs Pasadena campus.

Advanced mobility avionics : a reconfigurable mirco-avionics platform for the future needs of small planetary rovers and micospacecraft

Future small and micro-missions, such as Mars Scouts and Deep Space probes, require a new look at highly integrated, re-configurable, low power avionics. This paper will present our plans for developing a scalable, configurable, and highly integrated 32-bit embedded platform capable of implementing computationally intensive signal processing and control algorithms in space flight instruments and systems. This platform is designed to service the need of both small and large spacecraft and planetary rovers that will operate within moderate radiation environments. Some of the key characteristics of this platform are its small size, low power, high performance, and flexibility. This estimated 10 fold reduction in both size and power over state-of-the-art processing platforms will enable this new product to act as the core of a low-cost mobility system for a wide range of missions.