Sean M Murray, 3560 Woodside Cutoff Rd, Victor, MT 59875

6023698, Feb 8, 2000

Dec 5, 1996

8/759580

Anthony M. Lavey - Marietta GA
Rex Lavon Loftin - Smyrna GA
Sean T. Murray - Marietta GA
John M. Pisello - Rutledge GA

International Business Machines Corporation - Armonk NY

G06F 1730

707 10

A system and method for retrieving information from an online database. The system includes a server computer that is connected to a computer network, such as the Internet or an IP-based computer network. The server computer includes a server memory that stores token handler instructions, and a server processor that is responsive to the token handler instructions. A client computer includes a client memory that stores client application instructions and a client processor connected to the client processor. The client application instructions include a set of dynamic link libraries of code and information for each of a plurality of Internet service providers. The client processor is responsive to the client application instructions by establishing a connection with the server computer over the Internet through a selected Internet service provider and by sending tokens to the server computer. The connection to the Internet through the selected Internet service provider is based on a set of dynamic link libraries of code and information for the selected Internet service provider.

2022019, Jun 23, 2022

Apr 15, 2020

17/604285

- Boston MA, US
Sean Murray - Cambridge MA, US
Matthew Ryan - Milton MA, US
Arne Sieverling - Somerville MA, US

B25J 9/16

A processor-based system provides a user interface to facilitate generation of motion planning graphs or roadmaps, for example via autonomous generate of additional poses, for example neighboring poses, based on specified seed or origin pose, and/or generate or sub-lattice connecting poses and/or edges to couple separate regions or sub-lattices of the motion planning graph together. Such may include performing collision-checking and/or kinematic checking (e.g., taking into account kinematic constraints of robots being modeled). The resulting motion planning graphs or roadmaps are useful in controlling robots during runtime. Robots may include robots with appendages and/or robots in the form of autonomous vehicles.

2022017, Jun 9, 2022

Feb 28, 2022

17/682732

- Durham NC, US
- Providence RI, US
Sean MURRAY - Durham NC, US
George KONIDARIS - Durham NC, US
William WALKER - Durham NC, US

B60W 30/09
B60W 30/095
G05D 1/00
G05D 1/02
G06V 20/58

A motion planner of an autonomous vehicle's computer system uses reconfigurable collision detection architecture hardware to perform a collision assessment on a planning graph for the vehicle prior to execution of a motion plan. For edges on the planning graph, which represent transitions in states of the vehicle, the system sets a probability of collision with a dynamic object in the environment based at least in part on the collision assessment. Depending on whether the goal of the vehicle is to avoid or collide with a particular dynamic object in the environment, the system then performs an optimization to identify a path in the resulting planning graph with either a relatively high or relatively low potential of a collision with the particular dynamic object. The system then causes the actuator system of the vehicle to implement a motion plan with the applicable identified path based at least in part on the optimization.

2021022, Jul 22, 2021

Jan 20, 2021

17/153662

- Boston MA, US
Sean Murray - Cambridge MA, US

B25J 9/16
G06N 3/12

Solutions for multi-robot configurations are co-optimized, to at least some degree, across a set of non-homogenous parameters based on a given set of tasks to be performed by robots in a multi-robot operational environment. Non-homogenous parameters may include two or more of: the respective base position and orientation of the robots, an allocation of tasks to respective robots, respective target sequences and/or trajectories for the robots. Such may be executed pre-runtime. Output may include for each robot: workcell layout, an ordered list or vector of targets, optionally dwell time durations at respective targets, and paths or trajectories between each pair of consecutive targets. Output may provide a complete, executable, solution to the problem, which in the absence of variability in timing, can be used to control the robots without any modification. A genetic algorithm, e.g., Differential Evolution, may optionally be used in generating a population of candidate solutions.

2021002, Jan 28, 2021

Mar 19, 2019

16/981467

- Boston MA, US
George Konidaris - Boston MA, US
Sean Murray - Cambridge MA, US
William Floyd-Jones - Boston MA, US
Peter Howard - Boston MA, US
Xianchao Long - Boston MA, US

B25J 9/16
B25J 9/00
B25J 13/08
B25J 15/04
B25J 15/00
B25J 17/02

A robot control system determines which of a number of discretizations to use to generate discretized representations of robot swept volumes and to generate discretized representations of the environment in which the robot will operate. Obstacle voxels (or boxes) representing the environment and obstacles therein are streamed into the processor and stored in on-chip environment memory. At runtime, the robot control system may dynamically switch between multiple motion planning graphs stored in off-chip or on-chip memory. The dynamically switching between multiple motion planning graphs at runtime enables the robot to perform motion planning at a relatively low cost as characteristics of the robot itself change. Various aspects of such robot motion planning are implemented in particular systems and methods that facilitate motion planning of the robot for various environments and tasks.

2019024, Aug 8, 2019

Feb 5, 2019

16/268290

- Boston MA, US
George Konidaris - Boston MA, US
Sean Murray - Boston MA, US
William Floyd-Jones - Boston MA, US

B25J 9/16
G05D 1/02

A robot control system determines which of a number of discretizations to use to generate discretized representations of robot swept volumes and to generate discretized representations of the environment in which the robot will operate. Obstacle voxels (or boxes) representing the environment and obstacles therein are streamed into the processor and stored in on-chip environment memory. At runtime, the robot control system may dynamically switch between multiple motion planning graphs stored in off-chip or on-chip memory. The dynamically switching between multiple motion planning graphs at runtime enables the robot to perform motion planning at a relatively low cost as characteristics of the robot itself change.

2019021, Jul 18, 2019

Jan 4, 2019

16/240086

- Durham NC, US
William FLOYD-JONES - Durham NC, US
Sean MURRAY - Durham NC, US
George KONIDARIS - Durham NC, US
William WALKER - Durham NC, US

B60W 30/09
B60W 30/095
G06K 9/00
G05D 1/00
G05D 1/02

A motion planner of an autonomous vehicle's computer system uses reconfigurable collision detection architecture hardware to perform a collision assessment on a planning graph for the vehicle prior to execution of a motion plan. For edges on the planning graph, which represent transitions in states of the vehicle, the system sets a probability of collision with a dynamic object in the environment based at least in part on the collision assessment. Depending on whether the goal of the vehicle is to avoid or collide with a particular dynamic object in the environment, the system then performs an optimization to identify a path in the resulting planning graph with either a relatively high or relatively low potential of a collision with the particular dynamic object. The system then causes the actuator system of the vehicle to implement a motion plan with the applicable identified path based at least in part on the optimization.

2019016, May 30, 2019

Jun 9, 2017

16/308693

- Durham NC, US
George D. KONIDARIS - Durham NC, US
William FLOYD-JONES - Durham NC, US
Sean MURRAY - Durham NC, US

G05D 1/02
G06F 16/901
G05D 1/00

A system for motion planning for autonomous vehicles can include a plurality of sensors, a plurality of detectors in electrical communication with the plurality of sensors, and a motion planning module in electrical communication with the plurality of detectors and a computing system of an autonomous vehicle. The motion planning module stores a planning graph with each node representing, explicitly or implicitly, time and variables defining a state of the autonomous vehicle, an operating environment, or both the state of the autonomous vehicle and the operating environment. A reconfigurable processor can include a collision detection module and, optionally, a shortest path module. Pre-computed collision data and planning graph data reflecting logical/physical node mapping can be communicated to the processor during a programming phase and used during runtime.