| Autonomous Solutions, Inc. Patent applications |
| Patent application number | Title | Published |
|---|
| 20100065345 | METHOD AND APPARATUS FOR CONTROLLING TRACKED VEHICLES - Apparatus for controlling a track on a tracked vehicle may comprise a drive system, a clutch, a brake, and a track control system to operate the clutch and the brake. A control signal generator operatively associated with the track control system produces control signals that vary at a first rate to cause the track control system to transition the clutch from an engaged state to a disengaged state and produces control signals that vary at a second rate to cause the track control system to transition the brake from an initial application state to a full application state, the second rate being less than the first rate. | 03-18-2010 |
| 20100049374 | FOLLOWER VEHICLE CONTROL SYSTEM AND METHOD FOR FORWARD AND REVERSE CONVOY MOVEMENT - A vehicle control system for causing a follower vehicle to follow a leader may have a tether system mounted to the follower vehicle. The tether system may include a tether having an end adopted to be attached to the leader, a length sensor, and an angle sensor. A path tracking system operatively associated with the tether system determines a path traveled by the leader. A path control system operatively associated with the path tracking system and the follower vehicle causes the follower vehicle to follow the path traveled by the leader. A spacing control system operatively associated with the path tracking system and the follower vehicle causes the follower vehicle to maintain a predetermined spacing between the follower vehicle and the leader. | 02-25-2010 |
| 20090327011 | VEHICLE DISPATCHING METHOD AND SYSTEM - A system and method for dispatching a plurality of vehicles operating in a work area among a plurality of destination locations and a plurality of source locations includes implementing linear programming that takes in an optimization function and constraints to generate an optimum schedule for optimum production, utilizing a reinforcement learning algorithm that takes in the schedule as input and cycles through possible environmental states that could occur within the schedule by choosing one possible action for each possible environmental state and by observing the reward obtained by taking the action at each possible environmental state, developing a policy for each possible environmental state, and providing instructions to follow an action associated with the policy. | 12-31-2009 |
