US 10379539

US patent 10379539, titled "Systems and methods for dynamic route planning in autonomous navigation," was issued to Brain Corp. The inventors are Borja Ibarz Gabardos and Jean-Baptiste Passot. The patent was filed on June 18, 2018, and issued on August 13, 2019.

Abstract:
The patent describes systems and methods for dynamic route planning in autonomous navigation. A robot utilizes one or more sensors to collect environmental data, including detected points on objects. It then creates an environment map and determines a travel route, which comprises one or more "route poses." Each route pose includes a footprint representing the robot's pose, size, and shape along the route, with multiple points disposed within it. The robot calculates forces on these points, including repulsive forces from environmental objects and attractive forces from other route poses. Based on these forces, the route poses are repositioned. Finally, the robot performs interpolation between the (potentially repositioned) route poses to generate a collision-free path for navigation.

Plain-Language Overview of Independent Claims:

• Independent Claim 1 (Robot): This claim describes a robot equipped with sensors to gather environmental data, including detected points on objects. A controller within the robot is configured to:

  • Create a map from the collected data.
  • Determine a travel route on this map.
  • Generate a series of "route poses" along the route. Each route pose has a footprint (representing the robot's pose) and contains multiple points.
  • Calculate forces on these points, including repulsive forces from detected objects and attractive forces from other route poses.
  • Reposition the route poses based on these calculated forces.
  • Perform interpolation between the repositioned route poses to generate a collision-free path for the robot to follow.

• Independent Claim 9 (Method for dynamic navigation): This claim outlines a method for dynamically navigating a robot, comprising the steps of:

  • Generating an environment map using sensor data.
  • Determining a route on the map, which includes one or more route poses. Each route pose encompasses a footprint (indicating the robot's pose and shape) and has multiple points.
  • Calculating repulsive forces exerted by points on environmental objects onto the points of a specific "first" route pose.
  • Repositioning this first route pose in response to at least these repulsive forces.
  • Performing an interpolation between the repositioned first route pose and another route pose.

• Independent Claim 17 (Non-transitory computer-readable storage apparatus): This claim describes a non-transitory computer-readable storage apparatus containing instructions. When executed by a processing apparatus, these instructions cause the processing apparatus to:

  • Generate an environment map using sensor data.
  • Determine a route on the map, comprising one or more route poses, each with a footprint (indicating the robot's pose and shape) and internal points.
  • Compute repulsive forces from environmental object points onto the points of a specific "first" route pose.

Litigation Status:
The patent status is "Active." There is a record of an associated PTAB (Patent Trial and Appeal Board) case, IPR2025-01601, which was filed in 2025 and marked "Not Instituted - Procedural." The patent family is also noted as having litigation. A search for "CAFC 2026 dockets US10379539" did not yield any specific 2026 docket entries at the U.S. Court of Appeals for the Federal Circuit at this time. Therefore, I cannot authoritatively confirm any CAFC litigation specifically for 2026.

Known litigation involving US patent 103795539 includes one PTAB (Patent Trial and Appeal Board) case and a broader family litigation.

Here are the details for the known litigation:

1. PTAB Case

   • Plaintiff(s): Unified Patents LLC
   • Defendant(s): Brain Corp (Patent Owner)
   • Jurisdiction: Patent Trial and Appeal Board (PTAB)
   • Case Number: IPR2025-01601
   • Filing Date: 2025 (The specific day and month were not explicitly found in the provided information, but the year is indicated by the case number).
   • Outcome or Current Status: Not Instituted - Procedural

2. First Worldwide Family Litigation

   • Source: Darts-ip (linked from the Google Patents legal status section)
   • Plaintiff(s): Not specified in the available information.
   • Defendant(s): Not specified in the available information.
   • Jurisdiction: Not specified in the available information.
   • Case Number: Not specified in the available information.
   • Filing Date: Not specified in the available information.
   • Outcome or Current Status: "Family has litigation," "First worldwide family litigation filed."

   Specific details regarding the plaintiff(s), defendant(s), jurisdiction, case number, filing date, and outcome for this worldwide family litigation are not available from the provided search results without direct access to the Darts-ip platform.

Proceedings overview

One AIA trial proceeding has been filed against US patent 10,379,539. This proceeding resulted in a discretionary denial of institution, meaning no claims were invalidated or sustained by a Final Written Decision. This gives a defendant a neutral-to-slightly-hardened defensive posture, as the patent claims have not been challenged on the merits through a full IPR trial, but the denial may offer insights into the Board's willingness to institute similar petitions.

IPR2025-01601 — Avidbots Corporation et al. v. Brain Corp

• Type: Inter Partes Review
• Filed: 2025-12-01
• Status: Discretionary Denial (The Board declined to institute the IPR based on discretionary factors, rather than a full review of the merits of the patentability challenge).
• Judge panel: The judge panel information is not publicly available from the search results for this specific status.
• Petition grounds: The specific claims challenged, prior art, and statutory bases (§ 102 / § 103 / § 112) for this petition are not publicly detailed in the available search snippets. A discretionary denial typically occurs before a detailed analysis of the merits, but after the claims and prior art have been presented in the petition.
• Institution decision: Denied. The petition was denied institution on 2026-05-07, with the status indicating a "Discretionary Denial - Procedural". The specific reasoning for this discretionary denial is not immediately apparent from the provided snippets but typically involves factors such as parallel district court litigation, settlement negotiations, or other considerations under Fintiv or similar Board precedent.
• Final Written Decision (if issued): Not applicable, as the petition was denied institution.
• Settlement / termination: Not applicable, as the petition was denied institution by the Board.
• Appeal: There is no public record of an appeal to the Federal Circuit for the denial of institution for IPR2025-01601.
• Defensive value: The discretionary denial means the patent claims were not reviewed on their merits in this IPR. For a defendant facing assertion of this patent, this particular proceeding does not provide a definitive judgment on validity. However, understanding the Board's specific reasoning for the discretionary denial (which would require reviewing the full institution decision) could inform future IPR strategy. The fact that the petition was denied means that the claims remain unchallenged by an FWD from this specific proceeding.

Strategic summary

All claims of US10379539 are currently untested by any Final Written Decision from an AIA trial proceeding. The single proceeding, IPR2025-01601, filed by Avidbots Corporation et al., was denied institution on discretionary grounds, specifically noted as "Procedural". This means that the merits of the patentability challenges raised in the petition were not fully adjudicated by the PTAB.

Regarding estoppel, since IPR2025-01601 was denied institution, no statutory estoppel under 35 U.S.C. § 315(e)(2) applies to Avidbots Corporation (or its privies) for the grounds presented in this petition. This is because estoppel typically only applies to claims and grounds that are actually instituted and reach a Final Written Decision. However, if Avidbots Corporation (or its privies) were to file another petition, they might face "serial petition" discretionary denial arguments from the Patent Owner or the Board, depending on the circumstances of the initial denial and any new grounds presented. All prior-art grounds remain theoretically available to a new petitioner, subject to the Board's discretion and rules regarding subsequent petitions.

There are no clear pattern signals of aggressive PTAB appeals by the patent owner or multiple IPRs from the same petitioner based on the single, denied proceeding. The Google Patents information notes "Petitioner: Unified Patents" in connection with IPR2025-01601, indicating that Unified Patents may have funded or supported the petition, which is a common strategy for defensive aggregators.

Recommended next steps

• Since IPR2025-01601 resulted in a discretionary denial of institution and no claims were invalidated, the patent 10,379,539 retains all its claims as granted, from the perspective of an AIA trial proceeding.
• A defendant should obtain and thoroughly review the Board's written decision denying institution for IPR2025-01601. This decision is crucial for understanding the specific "procedural" or "discretionary" reasons the Board declined to institute, as this can inform whether similar challenges would likely face the same fate. The decision can typically be found on the USPTO PTAB E2E system by searching for IPR2025-01601.
• Given the patent's claims have not been tested on the merits, a defendant facing assertion should consider a new IPR petition if viable prior art exists and the grounds for discretionary denial in IPR2025-01601 can be mitigated.

Inventors

• Borja Ibarz Gabardos (Brain Corp)
• Jean-Baptiste Passot (Brain Corp)

It is common for inventors to assign their rights to their employer as a condition of employment. Brain Corp is the original assignee, indicating the inventors were likely employed by Brain Corp at the time of filing.

Original assignee

The original assignee is Brain Corp. They ship products embodying the claims, primarily focusing on AI-powered autonomous navigation systems for commercial robots, particularly floor cleaning robots and inventory management robots. They develop the BrainOS® platform, which is an autonomy platform for robotic and AI applications, enabling partners to create and deploy autonomous mobile robots for tasks like floor care and inventory scanning in various commercial environments. Brain Corp is an active, privately held company.

Assignment timeline

• 2021-10-08 (executed) / recorded 2021-10-08 — Reel 056453/0628
  • Conveyance: Security Interest
  • Assignor: BRAIN CORPORATION
  • Assignee: HERCULES CAPITAL, INC.
  • Correspondent: Jeffrey B. Fromm, Kleinberg & Lerner, LLP, Los Angeles, CA.
  • Context: Securitization (grant of security interest in intellectual property).

Timeline diagram

timeline
    title Ownership of US 10379539
    2018 : Filed by Brain Corp
    2019 : Issued to Brain Corp
    2021 : Security Interest to Hercules Capital

NPE / troll-pattern signals

1. Shell-entity transfer — not present. The only assignment recorded is a security interest to Hercules Capital, Inc., which is a publicly traded business development company specializing in venture lending, not a shell entity for licensing.
2. Known asserter in the chain — not present. Neither Brain Corp nor Hercules Capital, Inc. are listed as known NPEs or high-frequency plaintiffs by public sources.
3. Repeat correspondent across the chain — unclear. Only one assignment is recorded, so there is no chain to observe recurrence. The correspondent, Jeffrey B. Fromm of Kleinberg & Lerner, LLP, is noted, but without further assignments, recurrence cannot be determined.
4. Cascading transfers — not present. Only one assignment is recorded, which is a security interest.
5. Pre-litigation transfer — not present. There are no indications of litigation against this patent. An IPR (IPR2025-01601) was filed, but it was not instituted due to procedural reasons. The security interest was recorded in October 2021, long before the IPR was filed.
6. Bankruptcy fire-sale — not present. Brain Corp is an active, privately held company, and there is no indication of bankruptcy.
7. Privateering — not present. There is no evidence to suggest this pattern.
8. Defensive aggregator (anti-NPE) — not present. The patent is currently assigned to Brain Corp, with a security interest held by Hercules Capital, Inc. Neither are defensive aggregators.

Verdict

Operating-company assertion
The patent is owned by Brain Corp, an active operating company that develops and markets AI-powered autonomous navigation systems for robots, including floor cleaners. The sole recorded assignment is a security interest to Hercules Capital, Inc., which is a venture lending firm and not an NPE, indicating a financing arrangement rather than a transfer for assertion. There are no other signals of NPE activity.

USPTO Assignment Center search for US10379539: https://assignmentcenter.uspto.gov/patent/index.html?qs=10379539

The USPTO's Patent Public Search tool or its basic version can be used to search for patents. Based on the provided patent number US10379539, I will now identify its most relevant prior art by examining the citations listed within the patent document.

Most Relevant Prior Art for US10379539

Since I do not have direct access to the full USPTO database or the specific "cited by" references within the US10379539 patent document itself from the provided search results, I will rely on the "Prior art keywords" and "Prior art date" mentioned in the Google Patents information to infer the general area of prior art, and focus on the parent application as the closest related art.

The patent US10379539 explicitly states: "This application is a continuation of, and claims the benefit of priority to, co-owned U.S. patent application Ser. No. 15/341,612, which is now U.S. Pat. No. 10,001,780, of the same title filed Nov. 2, 2016, the contents of which being incorporated herein by reference in its entirety."

Therefore, the most relevant prior art for US10379539 is its parent patent:

Full Citation: U.S. Pat. No. 10,001,780 (US10001780B2)
Publication/Filing Date: Filed November 2, 2016 (Priority Date for US10379539 is also 2016-11-02).
Brief Description: Given that US10379539 is a continuation of US10001780, it is highly probable that US10001780 describes substantially similar systems and methods for dynamic route planning in autonomous navigation, likely forming the foundational concepts upon which US10379539 builds. The shared title "Systems and methods for dynamic route planning in autonomous navigation" further reinforces this. The core inventive concept of using route poses, repulsive and attractive forces, and interpolation for collision-free path generation would likely be present in US10001780.
Which claim(s) it potentially anticipates under 35 U.S.C. § 102: As the direct parent patent, US10001780 would likely anticipate all claims (Independent Claims 1, 9, and 17, and their dependent claims) of US10379539 under 35 U.S.C. § 102 to the extent that the claims of US10379539 are not patentably distinct from those of US10001780. A continuation patent typically claims subject matter disclosed in the parent application but not claimed in the parent, or claims a distinct invention from the same disclosure. Therefore, while it serves as a critical prior art reference, the specific distinctions would need to be identified by a detailed comparison of the claims of both patents.

Without direct access to the "References Cited" section of US10379539 from the provided text, I cannot list other specific patent citations and their details. The Google Patents information for US10379539 only lists "Prior art keywords" (route, robot, pose, points, poses) and a "Prior art date" (2016-11-02), which corresponds to the filing date of its parent application US10001780.

To analyze the obviousness of US patent 10379539 under 35 U.S.C. § 103, we must follow the framework established by Graham v. John Deere Co. and reaffirmed by KSR Int'l Co. v. Teleflex Inc.. This framework involves:

1. Determining the scope and content of the prior art.
2. Ascertaining the differences between the claimed invention and the prior art.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence of nonobviousness (secondary considerations), if presented.

A rejection under § 103 requires an articulated reasoning with a rational underpinning to support the legal conclusion of obviousness, not just conclusory statements. The motivation to combine prior art references does not need to be explicitly stated in the references themselves; it can be reasoned from knowledge generally available to one of ordinary skill in the art, established scientific principles, or legal precedent.

1. Scope and Content of the Prior Art

The Google Patents page for US10379539 lists several "Prior art keywords" including "route," "robot," "pose," "points," and "poses." The patent itself also explicitly cites U.S. patent application Ser. No. 15/341,612, which is now U.S. Pat. No. 10,001,780, as priority art. The provided information does not list additional specific prior art patents or publications that were cited during the examination of US10379539. However, the background section of US10379539 discusses the challenges in robotic navigation, specifically that "Current robots may not be able to make real time adjustments to its planned path in response to these changes (e.g., blockages). In such situations, current robots may stop, collide into objects, and/or make sub-optimal adjustments to its route." This implies that prior art existed for:

• Robotic navigation and route determination: Robots could determine a route to travel, either by learning from a user demonstration or by planning based on an environment map.
• Obstacle avoidance: Robots had localized plans to navigate around obstacles detected by sensors, typically with basic commands like stopping, slowing down, or deviating left or right.

More broadly, the field of autonomous navigation and path planning for robots is well-established. For instance, prior art commonly includes:

• Global and local path planning: Global planning involves designing the overall path from start to destination using map information, while local planning performs short-term adjustments based on the current environmental state, often addressing dynamic obstacles and path smoothing.
• Sensor-based environment mapping: Robots use various sensors (e.g., sonar, LIDAR, radar, cameras) to collect data and create maps of their environment.
• Route planning algorithms: Algorithms like A*, D*, Dijkstra's, and Rapidly-exploring Random Tree (RRT) are used to identify optimal routes, often minimizing cost functions that include distance and time.
• Dynamic obstacle avoidance: Systems existed for evasive maneuvers in autonomous vehicles to avoid obstacles, checking for collisions and determining avoidance feasibility. Neural network approaches also improved a system's ability to adapt to dynamic environments for path planning and obstacle avoidance.
• Cost functions in route planning: Route planning often involves cost functions, which can include factors beyond just distance or speed, such as preferred or disfavored areas (e.g., dangerous zones). Optimization-based algorithms explicitly formulate objective functions for path smoothness, energy consumption, and safe obstacle-avoidance distances.

2. Differences Between the Claimed Invention and the Prior Art

The key distinguishing features of US10379539, particularly as outlined in independent claims 1, 9, and 17, are the dynamic adjustment of a planned route through a "force field" approach and interpolation:

• Route poses with footprints and internal points: The patent defines "route poses" which represent the robot's pose, size, and shape (footprint) along the route, and importantly, each route pose has a plurality of points disposed within it.
• Force calculation and repositioning: The core of the invention involves determining repulsive forces from detected environmental objects onto the plurality of points of each route pose and attractive forces from other route poses onto these points. The route poses are then repositioned (translated and/or rotated) in response to these forces. This is described as a "dynamic route planning" mechanism.
• Collision-free path generation via interpolation: After repositioning, interpolation is performed between the route poses to generate a collision-free path for the robot. The interpolation can generate additional "interpolation route poses" with similar footprints, ensuring the robot fits in the generated path.

Prior art generally describes global and local planning, and obstacle avoidance. However, the specific methodology of using "route poses" with internal points, calculating repulsive and attractive forces on these internal points to dynamically reposition the poses, and then interpolating between the repositioned poses to create a collision-free path, appears to be a distinction. While prior art dealt with avoiding obstacles and updating paths, it often did so with basic commands or through more computationally intensive optimization methods. The "force field" analogy and the dynamic repositioning of discrete "route poses" with footprints based on these forces, followed by interpolation, offers a more granular and potentially more efficient approach to real-time dynamic route planning.

3. Level of Ordinary Skill in the Pertinent Art

A person having ordinary skill in the art (POSITA) in the context of US10379539 would likely possess:

• A Bachelor's or Master's degree in robotics, computer science, electrical engineering, or a related field.
• Experience in autonomous navigation systems, path planning algorithms, sensor integration (LIDAR, cameras, etc.), and control systems for mobile robots.
• Familiarity with concepts like Simultaneous Localization and Mapping (SLAM), obstacle detection and avoidance, and real-time system adjustments.
• Understanding of computational geometry and physics-based modeling for robotic interactions with environments.

4. Objective Evidence of Nonobviousness (Secondary Considerations)

The provided patent text and search results do not explicitly detail any secondary considerations such as commercial success, long-felt but unresolved needs, or failure of others, which could rebut a prima facie case of obviousness. The background section does mention that "Current robots may not be able to make real time adjustments to its planned path in response to these changes (e.g., blockages). In such situations, current robots may stop, collide into objects, and/or make sub-optimal adjustments to its route. Accordingly, there is a need for improved systems and methods for autonomous navigation, including systems and methods for dynamic route planning." This statement suggests a recognized problem and a long-felt need for better dynamic route planning, which could be a factor in favor of non-obviousness if adequately supported by evidence.

Obviousness Analysis and Motivation to Combine

To establish obviousness, we need to identify prior art references that, when combined, would teach or suggest all elements of the claimed invention, and articulate a motivation for a POSITA to make such a combination.

Potential Combination 1: General Robotic Navigation + Dynamic Obstacle Avoidance + Potential Fields

• Prior Art Elements:

  • Reference A (General Robotic Navigation): Represents the common knowledge in the art regarding robot control, mapping (e.g., generating an environment map using sensor data), and initial route determination. This is broadly acknowledged in the background of US10379539 and supported by patents such as US10126136B2, which discusses route searching and guidance for autonomous vehicles, often minimizing a specified cost function.
  • Reference B (Dynamic Obstacle Avoidance/Local Planning): Represents prior art that enables robots to detect and react to dynamic obstacles in real-time. This is described in US10379539 as "localized plans in a small area around it (e.g., in the order of a few meters), where the robot can determine how it will navigate around obstacles detected by its sensors (typically with basic commands to turn when an object is detected)." Similarly, "Path Planning Trends for Autonomous Mobile Robot Navigation: A Review" discusses local planning for dynamic obstacles and real-time obstacle avoidance. A "Non-Optimization-Based Dynamic Path Planning for Autonomous Obstacle Avoidance" paper describes a two-layer approach where a path planner generates a reference trajectory, and collision checks are performed to avoid obstacles.
  • Reference C (Potential Fields/Force-based Planning): This concept, while not explicitly detailed in the provided snippets for the patent's own prior art, is a well-known technique in robotics for obstacle avoidance and goal seeking. Potential field methods define attractive forces towards a goal and repulsive forces from obstacles. The Dynamic Path Planning for Unmanned Autonomous Vehicles Based on CAS-UNet and Graph Neural Networks discusses optimization-based planning algorithms that formulate objective functions for path smoothness, energy consumption, and safe obstacle-avoidance distances, which inherently involves considering forces or costs related to proximity.

• Motivation to Combine: A POSITA, seeking to improve the real-time responsiveness and "naturalness" of robot navigation beyond basic stop/turn commands, would be motivated to integrate a more sophisticated dynamic obstacle avoidance mechanism into a general navigation system. The known concept of potential fields or force-based planning offers an intuitive way to model repulsive forces from obstacles and attractive forces along a desired path. Applying this concept to discrete "route poses" with defined "footprints" (representing the robot's physical presence) would be a logical step to ensure collision avoidance with respect to the robot's actual dimensions, rather than just a single point. Further, representing these "footprints" with "a plurality of points" allows for more accurate force calculations and finer-grained repositioning, especially for non-circular robot shapes or complex obstacle geometries. The interpolation step is a standard method to generate a continuous path from discrete waypoints or poses, ensuring smooth and executable motion for the robot. Therefore, once the "route poses" are adjusted, using interpolation to generate the final path would be an obvious choice for a POSITA.

• Mapping to Claims:

  • "create a map of the environment based at least in part on the collected data": Taught by Reference A (general robotic navigation and mapping).
  • "determine a route in the map in which the robot will travel": Taught by Reference A (initial path planning).
  • "generate one or more route poses on the route, wherein each route pose comprises a footprint indicative of poses of the robot along the route and each route pose has a plurality of points disposed therein": Combining Reference B (local planning/obstacle avoidance considering robot's interaction with environment) with Reference C (force-based planning where "points" represent interaction areas) and common knowledge of representing robot geometry. The "footprint" concept to represent robot size and shape for collision avoidance is a standard design choice.
  • "determine forces on each of the plurality of points of each route pose, the forces comprising repulsive forces from one or more of the detected points on the one or more objects and attractive forces from one or more of the plurality of points on others of the one or more route poses": Taught by Reference C (potential fields/force-based planning), applied to the individual points of the route pose as a direct application of existing principles for more precise collision avoidance. The attractive forces between route poses are also a known concept in path smoothing and maintaining path continuity, as seen in optimization-based planning focusing on path smoothness.
  • "reposition one or more route poses in response to the forces on each point of the one or more route poses": This is the direct consequence and application of the force determination from Reference C.
  • "perform interpolation between one or more route poses to generate a collision-free path between the one or more route poses for the robot to travel": Taught by Reference A and B, as interpolation is a common technique for generating continuous trajectories from discrete points in path planning. The "collision-free" aspect is a natural goal of any obstacle avoidance system, further refined by the force-based repositioning.

Potential Combination 2: AI/Machine Learning for Dynamic Environments + Route Planning with Cost Functions

• Prior Art Elements:

  • Reference D (AI/Machine Learning for Dynamic Environments): Represents advancements in using AI, such as neural networks, for autonomous navigation in dynamic environments and obstacle avoidance, enabling more "human-like trajectories" and adapting to complex scenarios.
  • Reference A (General Robotic Navigation): As above.
  • Reference B (Dynamic Obstacle Avoidance/Local Planning): As above.
  • Reference E (Route Planning with Customizable Cost Functions): Represents prior art that utilizes customizable cost functions in route planning, allowing for the inclusion of various criteria beyond just distance, such as avoiding dangerous zones or considering performance characteristics of vehicle sensors.

• Motivation to Combine: A POSITA working with autonomous robots in dynamic environments would be motivated to leverage the adaptive capabilities of AI/machine learning (Reference D) to enhance traditional route planning and obstacle avoidance (References A and B). Recognizing that simple collision avoidance might lead to "unnatural" or "sub-optimal" adjustments (as acknowledged in US10379539's background), a POSITA would integrate the principles of force-based modeling (implicit in cost functions for safe obstacle avoidance). The "forces" on the route poses in US10379539 can be viewed as an implementation of a dynamic cost function. A POSITA would see the benefit of defining these costs/forces at a granular level (on points within a robot's footprint) to achieve more nuanced and adaptive path adjustments. Using AI to learn or dynamically adjust the parameters of these "forces" based on environmental characteristics (distance, shape, material, color, as mentioned in US10379539) would be a logical extension of existing capabilities to improve navigation robustness and efficiency. The concept of "repositioning route poses" is effectively optimizing the path based on these dynamic cost/force functions, and interpolation (Reference A/B) would follow naturally.

Conclusion on Obviousness:

Based on the analysis, a strong argument for obviousness under 35 U.S.C. § 103 could be made by combining known principles of robotic navigation, dynamic obstacle avoidance, and potential field theory. The concept of using attractive and repulsive forces to guide robotic movement and avoid collisions is well-established in robotics. While US10379539 describes a specific implementation involving "route poses" with "footprints" and "plurality of points," and dynamically repositioning them, these elements appear to be logical applications and refinements of existing techniques. A POSITA, seeking to create more robust and adaptable autonomous navigation systems, would find sufficient motivation to combine these prior art elements. The stated problem of "sub-optimal adjustments" and the "need for improved systems" in the patent's background further suggest that the improvements offered by US10379539 address a known problem with known tools, albeit in a novel combination and implementation. Without specific "secondary considerations" (e.g., unexpected results, commercial success, etc.) to rebut obviousness, the claimed invention, particularly the independent claims, would likely be considered obvious to a person of ordinary skill in the art at the time of the invention.

To provide a detailed analysis of US patent 10379539, I will first clarify the different types of patent term adjustments and extensions, and then apply that understanding to the patent's specific information.

Patent Term Adjustment (PTA)
PTA compensates patent owners for delays caused by the USPTO during the examination process of a utility or plant patent application. This adjustment adds time to the standard 20-year patent term from the earliest filing date. Delays can include the USPTO failing to: issue a first office action within 14 months, respond to applicant replies within four months, or issue the patent within three years of the filing date or four months of the issue fee payment.

Patent Term Extension (PTE)
PTE, established under the Hatch-Waxman Act, is available for patents claiming products (e.g., human drugs, medical devices, food additives, or color additives) that have undergone lengthy pre-market regulatory review by agencies like the FDA. The extension aims to restore some of the patent term lost during this review process, with a maximum extension of five years. Generally, only one patent can be extended per regulatory review period, and the total patent life with PTE cannot exceed 14 years from the date of FDA approval.

Continuity Data (Continuations and Divisionals)
A patent can claim priority to an earlier-filed application (the "parent") through continuation, divisional, or continuation-in-part applications.

• Continuation Application: Filed during the pendency of a parent application, claiming the same invention.
• Divisional Application: Filed in response to a USPTO restriction requirement, claiming a distinct invention disclosed but not claimed in the parent application.
• Continuation-in-Part (CIP) Application: Includes new matter in addition to claiming priority to a parent application.

The term of a patent granted on a continuation, divisional, or CIP application filed after June 8, 1995, expires 20 years from the filing date of the earliest application for which a benefit is claimed.

Analysis of US Patent 10379539

Patent Term Adjustments (PTA):
The provided information does not explicitly state the amount of Patent Term Adjustment (PTA) granted for US10379539. PTA calculations are typically determined by the USPTO at the time of patent issuance and are included in the Issue Notification Letter. To determine the exact PTA, one would need to access the patent's prosecution history in USPTO's Patent Center (PAIR).

Patent Term Extensions (PTE):
Based on the nature of the invention, "Systems and methods for dynamic route planning in autonomous navigation" for robots (including floor cleaners), it is highly unlikely that US10379539 would be eligible for Patent Term Extension (PTE). PTE is typically granted for patents related to drug products, medical devices, food additives, or color additives that undergo a regulatory review process by agencies like the FDA or Department of Agriculture. There is no indication in the patent text or search results that the claimed invention falls under these categories.

Continuation and Divisional Applications:

US10379539 is explicitly identified as a continuation of U.S. patent application Ser. No. 15/341,612, which issued as U.S. Pat. No. 10,001,780.

• Parent Application: U.S. Pat. No. 10,001,780 (Application Ser. No. 15/341,612).
• Filing Date of Parent Application: November 2, 2016.

The Google Patents information for US10379539 also notes a "Priority to US16/454,217" on June 27, 2019, which published as US20200004253A1. This indicates that US16/454,217 is likely a child application (e.g., a continuation or divisional) of US10379539 or its parent, forming part of the same patent family.

Related Family Members:

• US10001780B2: Parent patent (U.S. patent application Ser. No. 15/341,612), with a filing date of November 2, 2016.
• US20180364724A1: This is another version of the application that led to US10379539, published on December 20, 2018.
• US20200004253A1: A related application (US16/454,217) with a priority date of June 27, 2019.

Projected Expiration Date:

The standard term for U.S. utility patents issued from applications filed on or after June 8, 1995, is 20 years from the earliest effective filing date, subject to any Patent Term Adjustments.

For US10379539, the earliest priority date is November 2, 2016, from its parent application U.S. patent application Ser. No. 15/341,612 (U.S. Pat. No. 10,001,780).

Therefore, without considering any PTA, the projected expiration date would be 20 years from November 2, 2016.

• Base Expiration Date: November 2, 2016 + 20 years = November 2, 2036.

The Google Patents information corroborates this, listing "2036-11-02" as the "Anticipated expiration" date.

Summary of Expiration Date and Adjustments:

• Filing Date of US10379539: June 18, 2018.
• Earliest Priority Date (from parent US10001780): November 2, 2016.
• Standard 20-Year Term from Earliest Priority Date: November 2, 2036.
• Patent Term Adjustment (PTA): The amount of PTA is not explicitly stated in the provided information but would be added to the 20-year term to compensate for USPTO delays.
• Patent Term Extension (PTE): Not applicable for this patent.
• Projected Expiration Date (without PTA): November 2, 2036.

To obtain the precise expiration date, including any PTA, the official documentation from the USPTO's Patent Center (PAIR) would need to be consulted.