Robot Path Control for Predictive Dynamic Obstacle Avoidance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing robot technologies struggle to effectively avoid dynamic obstacles while moving to a target point, particularly in predicting and preventing collisions with external objects.
Innovation Solution
A robot control apparatus and method that utilizes sensors and processors to predict potential collisions by segmenting movement paths into sections, generating avoidance paths, and using algorithms like grid-based, graph-based, or sampling-based methods to navigate around obstacles, incorporating transit points and collision risk indexes to ensure safe operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the robot follows the shortest distance path to the target point, then the arrival time is minimized, but the collision risk with dynamic obstacles increases
Solution Approach 1:
The system performs preliminary actions by predicting the movement paths of dynamic obstacles before the robot reaches the collision zone. The processor calculates future positions of obstacles and pre-determines avoidance paths, allowing the robot to safely deviate from the shortest path in advance rather than reacting at the last moment. This maintains reliability while minimizing time loss.
Solution Approach 2:
The system dynamically adjusts the robot's path based on real-time obstacle predictions. Instead of following a fixed shortest path, the processor continuously calculates optimal avoidance routes by considering predicted obstacle positions, robot speed, and target location. This dynamic path adjustment resolves the contradiction by adapting the trajectory to balance speed and safety.
2Reliability
If the robot generates an avoidance path to prevent collision, then the safety is improved, but the movement distance and time increase
Solution Approach 1:
The system changes key parameters of the avoidance path, specifically the transit point location and path curvature. By optimizing these parameters, the processor generates avoidance paths that minimize deviation from the original shortest path. The transit point is strategically positioned to allow smooth transitions that reduce both distance and time penalties while maintaining safety.
Solution Approach 2:
The system applies partial avoidance action by only deviating from the shortest path when necessary. The processor evaluates collision risk and generates avoidance paths only when obstacles are detected, otherwise the robot follows the optimal shortest path. This selective approach minimizes the time and distance penalties while maintaining safety when needed.
3Measurement precision
If the robot segments the movement path into multiple sections for collision prediction, then the collision detection accuracy is improved, but the computational complexity increases
Solution Approach 1:
The system segments the movement path into multiple sections along the robot's trajectory. Each section is evaluated independently for potential collisions with predicted obstacle positions. This segmentation approach improves detection accuracy by examining specific path segments rather than the entire path at once, while the modular nature of segment evaluation keeps computational complexity manageable.
Solution Approach 2:
The system applies partial analysis by focusing computational resources only on path sections where collisions are likely. The processor identifies critical segments based on obstacle predictions and concentrates detailed collision checks on those areas, rather than uniformly analyzing the entire path. This reduces overall computational complexity while maintaining high detection accuracy where needed.
Data Source
AI summary
A robot control apparatus and a method thereof are provided. A robot control apparatus can include a sensor and a processor. The processor can determine whether an external object and a robot will collide with each other in a first path including a target point, based on identifying the external object using the sensor, while operating the robot along the first path, and can operate the robot along a second path for avoiding a collision between the robot and the external object, based on generating the second path. The first path can include a shortest distance path for causing the robot to move to the target point.