Obstacle Avoidance: Sensing, Path Planning, and Adaptation

All flashcards

What does obstacle avoidance mean?

It is a robot's or autonomous system's ability to detect obstacles and maneuver around them while continuing toward a predefined destination.

What information can obstacle-detection sensors provide?

Sensors can provide information about the environment, including the presence and distances of nearby objects.

What are effectors?

Effectors are tools or mechanisms that allow a robot to interact with its environment and carry out chosen actions.

What are the steps in the sense–think–act cycle?

The machine senses its surroundings, thinks by interpreting the data and choosing a response, and acts by using effectors to carry out that response.

How can machine learning support obstacle avoidance?

It can help a system adapt through repeated experience, including when environmental conditions change.

Quiz questions

1. How does path planning differ from reacting to an immediately detected obstacle?Answer: It considers a broader route connecting the robot's position and goal while accounting for obstacles.
2. What is the main purpose of Rapidly-exploring Random Trees (RRT) in path planning?Answer: To explore possible routes through a space.
3. How can machine learning help a robot navigating a changing environment?Answer: It can help the system adapt by learning from repeated experience.
4. Why can a fast-moving robot face greater risks during obstacle avoidance?Answer: It may not have enough time to sense, process, decide, and act before a hazard.
5. Why is it difficult to assess every possible orbital threat to a satellite?Answer: The large number of debris objects makes their timing and direction difficult to determine.