Difference between revisions of "JPL Robotics Meeting Notes"
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=== Mars rover autonomy === | === Mars rover autonomy === | ||
* combine approximate kinematic settling with a dual-cost path planner. | * combine approximate kinematic settling with a dual-cost path planner. | ||
| − | * develop multi-agent capabilities to significantly enhance performance | + | * develop multi-agent capabilities to significantly enhance performance - safety of autonomous operations on Mars. |
| − | * autonomy system to efficiently handle Mars' unpredictable terrain | + | * autonomy system to efficiently handle Mars' unpredictable terrain - improving mission success rates. |
* incorporate mechanisms for self-diagnosis and repair to ensure long-term functionality with minimal Earth-based support. | * incorporate mechanisms for self-diagnosis and repair to ensure long-term functionality with minimal Earth-based support. | ||
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* allowing for dynamic re-planning and risk management. | * allowing for dynamic re-planning and risk management. | ||
[[File:Screenshot13-16-39.png|400px|thumb|none]] | [[File:Screenshot13-16-39.png|400px|thumb|none]] | ||
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=== Advanced sensor integration === | === Advanced sensor integration === | ||
* high-resolution cameras and spectrometers | * high-resolution cameras and spectrometers | ||
Latest revision as of 22:50, 20 May 2024
User:vrtnis' notes from meeting with JPL robotics head of robotics team (EELS and Rover)
Contents
Mars rover autonomy[edit]
- combine approximate kinematic settling with a dual-cost path planner.
- develop multi-agent capabilities to significantly enhance performance - safety of autonomous operations on Mars.
- autonomy system to efficiently handle Mars' unpredictable terrain - improving mission success rates.
- incorporate mechanisms for self-diagnosis and repair to ensure long-term functionality with minimal Earth-based support.
Risk-aware planning[edit]
- utilize Boole's inequality for risk allocation.
- enhancing decision-making under uncertainty.
- employ predictive analytics to anticipate and mitigate potential risks.
- allowing for dynamic re-planning and risk management.
Advanced sensor integration[edit]
- high-resolution cameras and spectrometers
- integrate sensors for comprehensive environmental data.
- using ground-penetrating radar (GPR).
Humanoids[edit]
- for space exploration, utilizing human-like structure
- tasks requiring precise human-like movements.
- deploy humanoids for maintenance, repair enhancing astronaut safety.
- use in sample gathering/ environmental monitoring.
- simulate operations in space-like environments.
Energy[edit]
- optimize energy consumption.
- utilize a combination of solar panels.
- gather power from the environment, such as thermal gradients and mechanical movements.
[edit]
- utilize LIDAR
- optimal path planning
- integrate real-time obstacle detection
Project management lessons learned[edit]
- manage complex robotics projects like eels and Mars rovers by coordinating multiple teams
- advantage of having all team members colocated in the same building at the project's inception.
- more integrated workflows through initial colocation
- ensure alignment on project goals and timelines.
- early stages of complex projects benefit greatly from in-person collaboration. establish a strong foundation through colocation to enhance subsequent remote coordination efforts
