Abstract-Exploration of high risk terrain areas such as cliff faces and site construction operations by autonomous robotic systems on Mars requires a control architecture that is able to autonomously adapt to uncertainties in knowledge of the environment. We report on the development of a software/hardware framework for cooperating multiple robots performing such tightly coordinated tasks. This work builds on our earlier research into autonomous planetary rovers and robot arms. Here, we seek to closely coordinate the mobility and manipulation of multiple robots to perform examples of a cliff traverse for science data acquisition, and site construction operations including grasping, hoisting, and transport of extended objects such as large array sensors over natural, unpredictable terrain. In support of this work we have developed an enabling distributed control architecture called control architecture for multirobot planetary outposts (CAMPOUT) wherein integrated multirobot mobility and control mechanisms are derived as group compositions and coordination of more basic behaviors under a task-level multiagent planner. CAMPOUT includes the necessary group behaviors and communication mechanisms for coordinated/cooperative control of heterogeneous robotic platforms. In this paper, we describe CAMPOUT, and its application to ongoing physical experiments with multirobot systems at the Jet Propulsion Laboratory in Pasadena, CA, for exploration of cliff faces and deployment of extended payloads.
This paper describes a stereo vision-based system for autonomous navigation in maritime environments. The system consists of two key components. The Hammerhead vision system detects geometric hazards (i.e., objects above the waterline) and generates both grid-based hazard maps and discrete contact lists (objects with position and velocity). The R4SA (robust, real-time, reconfigurable, robotic system architecture) control system uses these inputs to implement sensor-based navigation behaviors, including static obstacle avoidance and dynamic target following. As far as the published literature is concerned, this stereo vision-based system is the first fielded system that is tailored for high-speed, autonomous maritime operation on smaller boats. In this paper, we present a description and experimental analysis of the Hammerhead vision system, along with key elements of the R4SA control system. We describe the integration of these systems onto a number of high-speed unmanned surface vessels and present experimental results for the combined vision-based navigation system. C
This paper describes a new sun sensor for absolute heading detection developed for the Field Integrated, Design and Operations (FIDO) rover. The FIDO rover is an advanced technology rover that is a terrestrial prototype of the rovers NASA/Jet Propulsion Laboratory (JPL) plans to send to Mars in 2003. Our goal was to develop a sun sensor that fills the current cost/performance gap, uses the power of subpixel interpolation, makes use of current hardware on the rover, and demands very little computational overhead. The need for a sun sensor on planetary rovers lies in the fact that current means of estimating the heading of planetary rovers involves integration of noisy rotational-speed measurements. This noise causes error to accumulate and grow rapidly. Moreover, the heading error affects the estimate of the and position of the rover. More importantly, incremental odometry heading estimation is only reliable over relatively short distances. There is an urgent need to develop a new heading-detection sensor for long traverses [for example, 100 m per Sol (Martian Day)], as requested for future Mars mission. Results of a recent FIDO field trial at Black Rock Summit in Central Nevada and several operations readiness tests at the JPL MarsYard using the sun sensor have demonstrated threefold to fourfold improvement in the heading estimation of the rover compared to incremental odometry.
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