Patle et al., 2023 - Google Patents
Optimal trajectory planning of the industrial robot using hybrid S-curve-PSO approachPatle et al., 2023
- Document ID
- 11594752486478825288
- Author
- Patle B
- Chen S
- Singh A
- Kashyap S
- Publication year
- Publication venue
- Robotic Intelligence and Automation
External Links
Snippet
Purpose The paper aims to develop an efficient and compact hybrid S-curve-PSO (particle swarm optimization) controller for the optimal trajectory planning of industrial robots in the presence of obstacles, especially those used in pick-and-place operations …
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/40—Robotics, robotics mapping to robotics vision
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0268—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/39—Robotics, robotics to robotics hand
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0255—Control of position or course in two dimensions specially adapted to land vehicles using acoustic signals, e.g. ultra-sonic singals
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0287—Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Mohanan et al. | A survey of robotic motion planning in dynamic environments | |
Ciocarlie et al. | Towards reliable grasping and manipulation in household environments | |
Patle et al. | Optimal trajectory planning of the industrial robot using hybrid S-curve-PSO approach | |
Kaldestad et al. | Collision avoidance with potential fields based on parallel processing of 3D-point cloud data on the GPU | |
Salan et al. | Minimum-energy robotic exploration: A formulation and an approach | |
Das Sharma et al. | Harmony search-based hybrid stable adaptive fuzzy tracking controllers for vision-based mobile robot navigation | |
Ahmad et al. | Learning to adapt the parameters of behavior trees and motion generators (btmgs) to task variations | |
Kecskés et al. | Multi-scenario multi-objective optimization of a fuzzy motor controller for the Szabad (ka)-II hexapod robot | |
Sharkawy | Intelligent control and impedance adjustment for efficient human-robot cooperation | |
Papp et al. | Navigation of differential drive mobile robot on predefined, software designed path | |
Rahul et al. | Deep reinforcement learning with inverse jacobian based model-free path planning for deburring in complex industrial environment | |
Alatartsev et al. | Robot trajectory optimization for the relaxed end-effector path | |
Suzuki et al. | Posture evaluation for mobile manipulators using manipulation ability, tolerance on grasping, and pose error of end-effector | |
Puiu et al. | Real-time collision avoidance for redundant manipulators | |
Sotiropoulos et al. | Rapid motion planning algorithm for optimal UVMS interventions in semi-structured environments using GPUs | |
Joshi et al. | Neuro-fuzzy based autonomous mobile robot navigation system | |
Cherroun et al. | Path following behavior for an autonomous mobile robot using neuro-fuzzy controller | |
AL-Nayar et al. | A comparative study for wheeled mobile robot path planning based on modified intelligent algorithms | |
Shang et al. | Fuzzy adaptive control of coal gangue sorting parallel robot with variable load | |
Pawlowski et al. | Trajectory optimization using learning from demonstration with meta-heuristic grey wolf algorithm | |
Krejsa et al. | Mobile robot motion planner via neural network | |
Payeur et al. | Robot path planning using neural networks and fuzzy logic | |
Salmaninejad et al. | Motion path planning of two robot arms in a common workspace | |
Krämer et al. | Comparing online robot joint space trajectory optimization for task space applications | |
Joshi et al. | Fuzzy based autonomous robot navigation system |