Tele-Robot Navigation With In-Situ Intelligence for Dynamic Environments
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Solution Overview
Problem
Tele-robots face challenges in navigating dynamic environments due to unpredictable movements and service disruptions, particularly in manual mode, and require efficient communication and in-situ intelligence to adapt to changing conditions.
Innovation Solution
A method and system for tele-robot navigation in dynamic environments using in-situ intelligence, which includes communication modes, Simultaneous Localization and Mapping (SLAM) techniques, spatial transforms, object detection, and Fast Marching Motion Planner (FMMP) for determining navigation policies, enabling the tele-robot to autonomously navigate through dynamic environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual mode navigation is used, then the master can directly control the tele-robot, but frequent transmission of kinematic control information is required which is inefficient in terms of communication resource usage
Solution Approach 1:
The tele-robot is equipped with in-situ intelligence that enables it to autonomously understand and adapt to dynamic environments, identify objects, estimate positions, and determine navigation policies without requiring constant master intervention. The robot serves itself by performing navigation tasks independently while maintaining the ability to receive high-level commands from the master.
2Loss of energy
If autonomous mode navigation is used, then communication resource usage is reduced, but service disruption probability increases due to loss of control commands because of transient impairments in the end-to-end channel
Solution Approach 1:
The system dynamically changes the degree of autonomy parameter based on communication conditions. When communication is reliable, the system operates in autonomous mode with reduced communication. When transient impairments occur, the system can transition to manual mode or semi-autonomous mode, adjusting the autonomy parameter to maintain service continuity while adapting to changing communication reliability.
3Measurement precision
If the tele-robot depends completely on the master's command, then control accuracy is maintained, but the tele-robot cannot adapt to unpredictable movements or positioning of objects obstructing the estimated trajectory in dynamic environments
Solution Approach 1:
The navigation control function is segmented into two independent components: high-level command generation from the master and low-level execution with in-situ intelligence at the tele-robot. This segmentation allows the master to provide accurate high-level guidance while the tele-robot independently handles real-time environmental adaptation, object detection, and trajectory adjustment, resolving the contradiction between control accuracy and environmental adaptability.
4Adaptability or versatility
If in-situ intelligent navigation is implemented, then adaptability to dynamic environments is improved, but device complexity increases due to the need for SLAM techniques, object detection, and motion planning algorithms
Solution Approach 1:
The in-situ intelligence system acts as an intermediary layer between the master and the tele-robot's motion execution. This intermediary handles the complex tasks of SLAM, object detection, and motion planning, shielding the master from complexity while enabling the tele-robot to adapt to dynamic environments. The intermediary processes sensor data, generates navigation policies, and executes commands, managing the system's complexity centrally.
Data Source
AI summary
This disclosure relates generally to navigation of a tele-robot in dynamic environment using in-situ intelligence. Tele-robotics is the area of robotics concerned with the control of robots (tele-robots) in a remote environment from a distance. In reality the remote environment where the tele robot navigates may be dynamic in nature with unpredictable movements, making the navigation extremely challenging. The disclosure proposes an in-situ intelligent navigation of a tele-robot in a dynamic environment. The disclosed in-situ intelligence enables the tele-robot to understand the dynamic environment by identification and estimation of future location of objects based on a generating/training a motion model. Further the disclosed techniques also enable communication between a master and the tele-robot (whenever necessary) based on an application layer communication semantic.