Caterpillar Inc.

Caterpillar Global Mining LLC

Philip Carl Wallstedt

Matthew D Johnson

Sagar Chowdhury

Joshua Struble

Kevin Anthony Davis

Karl Arthur Kirsch

Bryan James Everett

Emily Morris

Ananth Purushotham Kini

Eric John Schultz

Addwiteey Chrungoo

Manish Sharma

Sandesh Gowda

A method of automatically turning an autonomous mining truck (AMT), including front wheels and rear wheels, around in an operating area, including retrieving boundary data associated with the operating area, determining a first path to follow to execute a turn maneuver within the operating area based at least on the boundary data and dimensions of the AMT, wherein the first path includes a number of legs necessary to follow the first path through the turn maneuver, completing a first leg of the turn maneuver, determining a second path to follow and number of legs necessary to execute the turn maneuver based on an inability to execute the first path, and executing the second path to complete the turn maneuver.

Automatic steering of vehicle

Process for clearing an autonomous machine including first evaluating operation at a high curvature offline location. Following acceptable operation, the machine is placed into service and evaluated at a worksite. Following acceptable worksite operation, online operating speed of the machine is increased incrementally, and performance reevaluated. Following acceptable performance characteristics, online operating speed of the machine continues to be increased and revaluated until the machine reaches maximum designated operating speed, or is evaluated as unacceptable, in which case the machine continues to operate at the last acceptable online operating speed and identifies the unacceptable performance characteristic for further evaluation.

InCycle planner checkout for autonomous vehicles

A tracking problem detection system for a machine may include tracking diagnostic circuitry including one or more tracking diagnostic processors configured to receive a location signal indicative of a location of a machine and a path signal indicative of a path location associated with at least a portion of a path for the machine to follow while maneuvering. The tracking diagnostic processors may also be configured to determine a tracking difference between the path location and the location of the machine, and determine a frequency of a signal associated with the tracking difference and/or a frequency of a signal associated with a yaw rate associated with the maneuvering. The tracking diagnostic processors may also be configured to detect, based at least in part on the frequencies of the signals associated with the tracking difference and/or the yaw rate, a tracking problem associated with maneuvering the machine.

System and method for detecting tracking problems

A control system for preventing vehicle collisions may include a vehicle location determination module, a terrain determination module, a terrain surface coefficient of friction estimation module, and a sensing system configured to generate signals indicative of vehicle speed, vehicle pose, vehicle size, vehicle weight, vehicle tire type, vehicle load, vehicle gear ratio, weather characteristics, and road conditions for a vehicle operating at a job site. A manned vehicle trajectory determination module may receive location information and plot a first travel path for a manned vehicle based at least in part on a location, heading, and speed of the manned vehicle and a desired destination for the manned vehicle. An autonomous vehicle trajectory determination module may receive location information, terrain information, and terrain surface coefficient of friction information, plot a second travel path for an autonomous vehicle, and determine projected slide trajectories for the autonomous vehicle at successive positions along the second travel path where the autonomous vehicle is predicted to lose traction based at least in part on signals received from the sensing system.

System and method for avoiding contact between autonomous and manned vehicles caused by loss of traction

A speed planning device is disclosed. The speed planning device may perform a method including obtaining elevation information associated with a route for a vehicle; identifying a section of the route based on the elevation information, wherein the section is associated with a change in elevation; determining subsections of the section; determining respective slopes of the subsections and respective lengths of the subsections; obtaining information identifying a mass associated with the vehicle; generating a speed plan for the vehicle to traverse the section, wherein the speed plan indicates one or more speeds at which the vehicle is to correspondingly traverse the subsections based on the respective slopes of the subsections, the respective lengths of the subsections, and the mass associated with the vehicle; and providing the speed plan to permit the vehicle to be controlled to traverse the section according to the one or more speeds of the speed plan.

Speed planning device for a vehicle

A soft underfoot conditions response system for use with a vehicle includes a plurality of sensors configured to transmit signals indicative of live data representing at least one of real time vehicle speed, vehicle acceleration, vehicle pose, vehicle payload, engine torque, engine power output, and engine RPM, and a controller communicatively coupled with the sensors. The controller is programmed to receive the live data, receive reference data representative of soft underfoot conditions from a database, and analyze the live data and the reference data. The controller determines a first set of parameters including measured real time values corresponding to wheel slip ratio and rolling resistance, vehicle speed, and vehicle pose, extracts from the reference data at least one of a first data subset containing vehicle operational parameters identified by an operator as being associated with soft underfoot conditions, and a second data subset containing data extracted using heuristics, and builds and trains a model for use by a classifier that segregates data subsets from the first set of parameters into a first classification that includes parameters that characterize surfaces with soft underfoot conditions, and a second classification that includes parameters that characterize surfaces without soft underfoot conditions. The controller also generates control command signals that cause a change in vehicle operational parameters to reduce or avoid any effects on operation of the vehicle associated with soft underfoot conditions.

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Washington, IL, United States of America

Philip Carl Wallstedt