Small robots have the potential to access confined spaces where humans cannot go. However, the mobility of wheeled and tracked systems is severely limited in cluttered environments. Snake robots using biologically inspired gaits for locomotion can provide better access in many situations, but are slow and can easily snag. This paper introduces an alternative approach to snake robot locomotion, in which the entire surface of the robot provides continuous propulsive force to significantly improve speed and mobility in many environments.
This paper revisits the underlying mathematics behind Differential Correction, also called Orbit Determination (OD) and the derivation of the Extended Kalman Filter (EKF). Specifically, we explore the formulation in the context of satellite OD using either ground based or space based sensor measurements to update the satellite state vector. We use a slightly different approach for the partial derivative measurement matrix H. It is observed that for a six state, non-maneuvering satellite, the state transition matrix F of the EKF can be implemented as a truly linear model (derived from pure kinematics) or a linearized model whose elements are the partial derivatives of the nonlinear equation of motion with respect to the EKF state. However, for the measurement matrix H, the numerical accuracy of its elements (as partial derivatives of measurements with respect to the EKF state vector) plays a critical role in the overall accuracy. Two primary factors affecting the "quality" of the H matrix condition are the information dimension (i.e., 2 or 3 rows depending on the observations) and relative dynamics (i.e., from the sensor platform to the satellite platform) observability information captured by the sensor. The theoretical observability matrix required for the ODS filter to converge is evaluated and illustrated from simulated measurements. A combination of Matlab based simulation for the EKF implementation and AGI's Orbit Determination Tool Kit (ODTK) are used to investigate the observability issue and evaluate the EKF based OD performance. For the ODTK environment, actual ground based measurements data were employed to reconstruct the orbit of a commercial GEO satellite. The ODS solution accuracies are observed to be acceptable under these selected testing conditions/scenarios.
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.
SAICThis paper describes an approach to autonomous robotic control that enables cooperative, tactically correct robotic behaviors that human teammates understand. For maximum effectiveness, unmanned systems (UMSs) must be able to support dismounted warfighters in high-intensity, high-operational-tempo (OPTEMPO) situations without becoming a source of distraction. Current models of robotic control require overt human tasking, limiting robotics to low OPTEMPO tasks. The Combat Causal Reasoner (CCR) proposes to change the paradigm of UMS autonomy by enabling UMSs to cooperate with humans without expecting the UMS to perceive the environment as a human would. CCR uses a Playbook approach to generate responses that are consistent with warfighter actions. An experiment demonstrated that a CCRenabled robot measurably increased warfighter effectiveness and resource utilization, with no loss of robot effectiveness when compared to human tele-operation during high-tempo operations.
With the increased use of specialized robots within heterogeneous robotic teams, as envisioned by DARPA's Tactical Mobile Robotics program, the task of dynamically assigning work to individual robots becomes more complex and critical to mission success. The team must be able to perform all essential aspects of the mission, deal with dynamic and complex environments, and detect, identify, and compensate for failures and losses within the robotic team. Our mission analysis of targeted military missions has identified single-robot roles, and collaborative (heterobotic) roles for the TMR robots. We define a role as a set of activities or behaviors that accomplish a single, militarily relevant goal. We will present the use of these roles to: 1) identify mobility and other requirements for the individual robotic platforms; 2) rate various robots' efficiency and efficacy for each role; and 3) identify which roles can be performed simultaneously and which cannot. We present a role-base algorithm for tasking heterogeneous robotic teams, and a mechanism for retasking the team when assets are gained or lost.
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