Karl Murphy

Path planning for autonomous vehicles driving over rough terrain

This paper presents a multiresolutional architecture of planners for obstacle avoidance in outdoor mobility. The planner makes use of off-line dynamical simulations results to efficiently find paths that avoid obstacles. The trajectories are generated by sets of steering velocity commands. This approach of building the search space for the planner results in realistic cost and trajectories for the vehicle. An implementation of the planner was developed and tested in a vehicle at the National Institute of Standards and Technology (NIST) with promising results.

Driving autonomously off-road up to 35 km/h

A robotic highly mobile multipurpose wheeled vehicle drives autonomously off-road at speeds up to 35 km/h (10 m/s, 20 mph). The key features of the implementation that enable the vehicle driving at these speeds are: 1) planning the next 20 m with dynamically feasible trajectories; and 2) increasing the lateral clearance to obstacles at higher speeds. Clothoid trajectories are used in planning the vehicles immediate path. The speed-indexed clearance requirement improves the safety margin for the vehicle over a range of speeds while retaining the ability to maneuver in close quarters when necessary.

High-level mobility controller for a remotely operated unmanned land vehicle

The U.S. Army Laboratory Command, as part of the Department of Defense Robotics Testbed Program, is developing a testbed for cooperative, real-time control of unmanned land vehicles. The program entails the development and integration of many elements which allow the vehicles to perform both autonomous and teleoperated functions. The National Institute of Standards and Technology (NIST) is supporting this program by developing the vehicle control system using the Real-time Control System (RCS) architecture. RCS is a hierarchical, sensory-based control system, initially developed for the control of industrial robots and automated manufacturing systems. NIST is developing the portions of RCS that control all vehicle mobility functions, coordinate the operations of the other subsystems on the vehicle, and communicate between the vehicle and the remote operator control station. This paper reviews the overall control system architecture, the design and implementation of the mobility and communication functions, and results from recent testing.

Control system architecture for a remotely operated unmanned land vehicle

Techbase Enhancements for Autonomous Machines (TEAM) is a joint effort among several US Army organizations, national laboratories, and commercial contractors to develop a vehicle control system that can support a mix of capabilities ranging from master-slave teleoperation to autonomous control. The overall TEAM control system architecture and the design of the mobility and communication functions are described. The architecture is based on the real-time control system (RCS), a hierarchical, sensory-based control system. In this application, RCS controls all vehicle mobility functions, coordinates the operations of the other subsystems on the vehicle, and communicates between the vehicle and the remote operator control station. The functional modules of the control system and their responsibilities are described, with emphasis placed on the modules that support mobility functions. The design of the mobility and communication subsystems and the implementation of the mobility and communication control systems are outlined.<<ETX>>

GPS aided retrotraverse for unmanned ground vehicles

A computer controlled HMMWV automatically retraces a previously recorded path using navigation data, a process we have termed retrotraverse. A Kalman filter combines the output of two navigation systems, an inertial dead reckoning systems and a differential GPS both with and without carrier phase detection. During retrotraverse, the mobility controller uses a velocity controller and pure pursuit steering. Obstacles such as another vehicle can be detected with a laser range imaging device.

Reconnaissance and Autonomy for Small Robots (RASR) team: MAGIC 2010 challenge

The Reconnaissance and Autonomy for Small Robots (RASR) team developed a system for the coordination of groups of unmanned ground vehicles (UGVs) that can execute a variety of militarily relevant missions in dynamic urban environments. Historically, UGV operations have been primarily performed via teleoperation, requiring at least one dedicated operator per robot, and requiring substantial real-time bandwidth to accomplish those missions. Our team goal for entering the MAGIC 2010 competition was to develop a system that can provide practical long-term value to the war-fighter. To that end, we self-imposed a set of constraints that would force us to develop technology that could readily be used by the military in the near term: Use a relevant (deployed) platform Use low-cost, reliable sensors Develop an expandable and modular control system with innovative software algorithms to minimize the computing footprint required Minimize required communications bandwidth and handle communication losses Minimize additional power requirements to maximize battery life and mission duration © 2012 Wiley Periodicals, Inc.

Cleaning and Deburring Workstation operations manual

Certain commercial equipment is identified in this paper to adequately describe the systems under development. Such identification does not imply recommendation or endorsement by the National Bureau of Standards, nor does it imply that the equipment is the necessarily the best available for the purpose.

Results and conclusions: perception sensor study for high speed autonomous operations

Previous research has presented work on sensor requirements, specifications, and testing, to evaluate the feasibility of increasing autonomous vehicle system speeds. Discussions included the theoretical background for determining sensor requirements, and the basic test setup and evaluation criteria for comparing existing and prototype sensor designs. This paper will present and discuss the continuation of this work. In particular, this paper will focus on analyzing the problem via a real-world comparison of various sensor technology testing results, as opposed to previous work that utilized more of a theoretical approach. LADAR/LIDAR, radar, visual, and infrared sensors are considered in this research. Results are evaluated against the theoretical, desired perception specifications. Conclusions for utilizing a suite of perception sensors, to achieve the goal of doubling ground vehicle speeds, is also discussed.

Sensor study for high speed autonomous operations

As robotic ground systems advance in capabilities and begin to fulfill new roles in both civilian and military life, the limitation of slow operational speed has become a hindrance to the wide-spread adoption of these systems. For example, military convoys are reluctant to employ autonomous vehicles when these systems slow their movement from 60 miles per hour down to 40. However, these autonomous systems must operate at these lower speeds due to the limitations of the sensors they employ. Robotic Research, with its extensive experience in ground autonomy and associated problems therein, in conjunction with CERDEC/Night Vision and Electronic Sensors Directorate (NVESD), has performed a study to specify system and detection requirements; determined how current autonomy sensors perform in various scenarios; and analyzed how sensors should be employed to increase operational speeds of ground vehicles. The sensors evaluated in this study include the state of the art in LADAR/LIDAR, Radar, Electro-Optical, and Infrared sensors, and have been analyzed at high speeds to study their effectiveness in detecting and accounting for obstacles and other perception challenges. By creating a common set of testing benchmarks, and by testing in a wide range of real-world conditions, Robotic Research has evaluated where sensors can be successfully employed today; where sensors fall short; and which technologies should be examined and developed further. This study is the first step to achieve the overarching goal of doubling ground vehicle speeds on any given terrain.

3D printed rapid disaster response

Under the Department of Homeland Security-sponsored Sensor-smart Affordable Autonomous Robotic Platforms (SAARP) project, Robotic Research, LLC is developing an affordable and adaptable method to provide disaster response robots developed with 3D printer technology. The SAARP Store contains a library of robots, a developer storefront, and a user storefront. The SAARP Store allows the user to select, print, assemble, and operate the robot. In addition to the SAARP Store, two platforms are currently being developed. They use a set of common non-printed components that will allow the later design of other platforms that share non-printed components. During disasters, new challenges are faced that require customized tools or platforms. Instead of prebuilt and prepositioned supplies, a library of validated robots will be catalogued to satisfy various challenges at the scene. 3D printing components will allow these customized tools to be deployed in a fraction of the time that would normally be required. While the current system is focused on supporting disaster response personnel, this system will be expandable to a range of customers, including domestic law enforcement, the armed services, universities, and research facilities.