Off-road robotics efforts such as DARPA's PerceptOR program have motivated the development of testbed vehicles capable of sustained operation in a variety of terrain and environments. This paper describes the retrofitting of a minimally-modified ATV chassis into such a testbed which has been used by multiple programs for autonomous mobility development and sensor characterization. Modular mechanical interfaces for sensors and equipment enclosures enabled integration of multiple payload configurations. The electric power subsystem was capable of short-term operation on batteries with refueled generation for continuous operation. Processing subsystems were mounted in sealed, shock-dampened enclosures with heat exchangers for internal cooling to protect against external dust and moisture. The computational architecture was divided into a real-time vehicle control layer and an expandable high level processing and perception layer. The navigation subsystem integrated real time kinematic GPS with a three-axis IMU for accurate vehicle localization and sensor registration. The vehicle software system was based on the MarsScape architecture developed under DARPA's MARS program. Vehicle mobility software capabilities included route planning, waypoint navigation, teleoperation, and obstacle detection and avoidance. The paper describes the vehicle design in detail and summarizes its performance during field testing.
A multi-arm robotic testbed for space servicing applications is presented. The system provides the flexibility for autonomous control with operator interaction at different levels of abstraction. We have integrated key technologies from the areas of artificial intelligence, robotic control, computer vision, and human factors in an architecture which has proven useful for resolving issues related to space-based servicing tasks. A system-level breakdown of testbed components is presented, outlining the function and role of each technology area. A key feature of the architecture is that it facilitates efficient transfer of teleoperation control to all levels in the system hierarchy, enabling the study of the relationship between the human operator and the remote system. This includes the ability to perform autonomous situation assessment so that operator control activities at lower levels can be interpreted in terms of system model updates at higher levels.
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