Multiaxial Robot Path Generation Using Dynamic Velocity Patterns
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Solution Overview
Problem
Current methods for controlling the acceleration and deceleration of multiaxial robots are inefficient, as they fail to maximize movement velocity due to linear acceleration patterns and ignore constraint conditions, leading to suboptimal performance and increased time duration.
Innovation Solution
A method is developed to generate a path for multiaxial robots by specifying start and end points and calculating velocity patterns for joints, taking into account constraint conditions such as maximum acceleration, deceleration, velocity, and torque, while setting initial pass points to optimize the movement path and reduce inertia, allowing for increased acceleration and deceleration forces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a trapezoidal velocity pattern with constant acceleration is used, then the control is simple, but the motors cannot sufficiently exert their performances because the maximum acceleration changes in a non-linear manner with robot posture
Solution Approach 1:
The patent applies dynamics by transitioning from a static, constant acceleration trapezoidal velocity pattern to a dynamic acceleration pattern that varies with robot posture. The acceleration is calculated in real-time based on the current joint angles and robot configuration, allowing the acceleration profile to adapt dynamically to changing inertial properties and gravitational effects throughout the motion trajectory.
Solution Approach 2:
The patent changes the acceleration parameter from a constant value to a variable value that depends on robot posture. By calculating acceleration as a function of joint angles and using trigonometric relationships to account for gravitational and inertial effects at different positions, the system optimizes motor performance utilization throughout the entire motion range.
2Speed
If bang-bang control with maximum torque pattern is used, then the movement velocity can be increased, but constraint conditions such as upper limit of movement velocity are ignored
Solution Approach 1:
The patent implements feedback by continuously monitoring the robot's actual velocity and acceleration during motion execution. The calculated velocity pattern serves as a reference trajectory, and the control system adjusts the actual motor torques to ensure the robot follows this trajectory while respecting velocity and acceleration constraints. This closed-loop approach ensures constraint compliance while achieving high-speed motion.
Solution Approach 2:
The patent applies preliminary action by pre-calculating the optimal velocity and acceleration patterns before motion execution. The velocity pattern is computed in advance based on the desired trajectory and robot dynamics, incorporating all constraint conditions. This pre-planned pattern guides the real-time control, ensuring constraints are satisfied from the outset while maximizing motion speed.
3Ease of operation
If acceleration is increased at a constant rate based on weight and inertia, then the control is simplified, but the acceleration cannot go beyond the limitation imposed by the attributes of the trapezoidal velocity pattern
Solution Approach 1:
The patent transitions from static acceleration planning to dynamic acceleration planning that adapts to the robot's instantaneous posture. By calculating acceleration as a function of joint angles and using trigonometric relationships to account for gravitational and inertial effects at different positions, the system achieves higher acceleration capabilities while maintaining reasonable control complexity through systematic calculation methods.
4Adaptability or versatility
If discrete parameter curves are provided for each axis and movement direction, then the parameters can be set individually, but the management becomes troublesome and the parameters cannot precisely conform to the acceleration curve
Solution Approach 1:
The patent creates a universal acceleration calculation methodology that can be applied to all axes and movement directions of the robot through a single set of dynamic equations. Rather than managing separate discrete parameter curves for each axis, the system uses a unified approach based on robot dynamics and trigonometric relationships that automatically adapts to any joint or link, simplifying parameter management while maintaining full customization capability.
Data Source
AI summary
In a multiaxial robot, a path along which the end effector of the robot moves in the shortest time duration is generated. The robot includes a first link and a second link positioned closer to an end effector than the first link. Start and end points are specified, and velocity patterns are generated for joints driving the first and second links based on the specified start end points. The velocity patterns enable a movement of the second link to cause i) a reaction for increasing an acceleration force generated by the first joint when the end effector is started to be moved from the start point toward the end point, and ii) a reaction for increasing a deceleration force generated by the first joint when the end effector is stopping to the end point.