IP Library Granted Patent US 12,447,610
Granted Patent B2
US 12,447,610 · App. 18/161,142 · Granted Oct 21, 2025

Method for controlling a robotic device

Inventors: Philipp Christian Schillinger (Renningen, DE); Akshay Dhonthi Ramesh Babu (Ingolstadt, DE); Leonel Rozo (Boeblingen, DE)
Assignee: ROBERT BOSCH GMBH
B25J9/163B25J9/1653B25J9/1661B25J13/08
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Quick Facts
Patent No.
US 12,447,610
App. No.
18/161,142
Granted
Oct 21, 2025
Kind
B2
Abstract

A method of controlling a robotic device. The method includes generating a robot control model for performing a task, wherein the robot control model comprises parameters which influence the performance of the task, adjusting the parameters of the robot control model by optimizing a target function which evaluates the adherence to at least one condition with respect to the temporal progression of at least one continuous sensor signal when performing the task, and controlling the robotic device according to the robot control model in order to perform the task using the adjusted parameters.

Claims (24)

1. A method for controlling a robotic device, the method comprising the following steps:

generating a robot control model for performing a task, wherein the robot control model includes parameters which influence the performance of the task;

adjusting the parameters of the robot control model by optimizing a target function which evaluates the adherence to at least one condition with respect to a temporal progression of at least one continuous sensor signal when performing the task;

representing the at least one condition according to temporal signal logic in at least one temporal signal logic formula;

converting the at least one temporal signal logic formula into at least one measure of robustness;

evaluating the target function by determining a value of the at least one measure of robustness for performing the task; and

controlling the robotic device according to the robot control model to perform the task using the adjusted parameters.

2. The method according to claim 1 , wherein the parameters of the robot control model include time-related parameters and location-related parameters.

3. The method according to claim 1 , wherein the robot control model is a hidden semi-Markov model (HSMM).

4. The method according to claim 1 , wherein the at least one continuous sensor signal indicates a location of a portion of the robotic device and/or a force acting on a portion of the robotic device.

5. A robot control device configured to control a robotic device, the robotic device configured to:

generate a robot control model for performing a task, wherein the robot control model includes parameters which influence the performance of the task;

adjust the parameters of the robot control model by optimizing a target function which evaluates the adherence to at least one condition with respect to a temporal progression of at least one continuous sensor signal when performing the task;

represent the at least one condition according to temporal signal logic in at least one temporal signal logic formula;

convert the at least one temporal signal logic formula into at least one measure of robustness;

evaluate the target function by determining a value of the at least one measure of robustness for performing the task; and

control the robotic device according to the robot control model to perform the task using the adjusted parameters.

6. A non-transitory computer-readable medium on which is stored a computer program for controlling a robotic device, the computer program, when executed by a processor, causing the processor to perform the following steps:

generating a robot control model for performing a task, wherein the robot control model includes parameters which influence the performance of the task;

adjusting the parameters of the robot control model by optimizing a target function which evaluates the adherence to at least one condition with respect to a temporal progression of at least one continuous sensor signal when performing the task;

representing the at least one condition according to temporal signal logic in at least one temporal signal logic formula;

converting the at least one temporal signal logic formula into at least one measure of robustness;

evaluating the target function by determining a value of the at least one measure of robustness for performing the task; and

controlling the robotic device according to the robot control model to perform the task using the adjusted parameters.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 6, 2023
From: SCHILLINGER, PHILIPP CHRISTIAN; DHONTHI RAMESH BABU, AKSHAY; ROZO, LEONEL
To: ROBERT BOSCH GMBH
Reel/Frame 062599/0928 →
Priority Claims (1)
DE 10 2022 201 116.3 · Feb 2, 2022 · national
Continuity (1)
Related Publication 20230241772A1 · Aug 3, 2023
References Cited (17)
US 20160246929A1 · Zenati · 2016 [cited by examiner]
US 20200398427A1 · Kupcsik · 2020 [cited by examiner]
US 20210125052A1 · Tremblay et al. · 2021 [cited by applicant]
US 20210334696A1 · Traut · 2021 [cited by examiner]
US 20220299949A1 · Oyama · 2022 [cited by examiner]
DE 102019001207A1 · 2019 [cited by applicant]
DE 102019203634A1 · 2020 [cited by applicant]
DE 102019207410A1 · 2020 [cited by applicant]
DE 102019216229A1 · 2021 [cited by applicant]
DE 102020206916A1 · 2021 [cited by applicant]
DE 102020207085A1 · 2021 [cited by applicant]
DE 102020209685A1 · 2022 [cited by applicant]
EP 3587045A1 · 2020 [cited by applicant]
EP 3753684A1 · 2020 [cited by applicant]
Rozo et al., “Learning and Sequencing of Object-Centric Manipulation Skills for Industrial Tasks,” 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020, pp. 9072-9079. [cited by applicant]
Innes et al., “Elaborating on Learned Demonstrations With Temporal Logic Specifications,” Cornell University, 2020, pp. 1-10. [cited by applicant]
Dhonthi et al., “Study of Signal Temporal Logic Robustness Metrics for Robotic Tasks Optimization”, Cornell University, 2021, pp. 1-3. [cited by applicant]