Page 83 - Robotics and AI class 10
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For example, in autonomous, self driving cars or drones, LiDAR sensors are used for mapping, localisation, and
            obstacle detection. The LiDAR sensor scans the environment, creating a 3D map that includes information about
            the position and shape of objects. This map can be used for localisation, allowing the robot to determine its
            position within the mapped environment. Additionally, the LiDAR sensor can detect obstacles by identifying
            objects or changes in the environment, enabling collision avoidance and safe navigation.
            LiDAR sensors are particularly effective in environments where accurate distance measurements and detailed 3D
            mapping are required, such as outdoor navigation, warehouse automation, or autonomous vehicle applications.
            They provide reliable spatial information that helps robots understand their surroundings and make informed
            navigation decisions.

            Speech Recognition Sensor

            This although not strictly categorised as a sensor, is a technology used
            in robotics to convert spoken language into written text or commands. It
            enables robots to understand and respond to human speech, facilitating
            natural and intuitive human-robot interaction. Speech recognition
            systems analyse the audio input, identify spoken words or phrases, and
            convert them into text or actionable commands. Let’s explore an example
            of  speech  recognition  technology  used  in  robotics:  voice-controlled
            personal assistants.
            Voice-controlled personal assistants, such as Amazon’s Alexa, Google Assistant, or Apple’s Siri, utilise speech
            recognition technology to understand and respond to user commands or queries. These assistants are embedded
            in devices such as smart speakers, smartphones, or home automation systems.

            For instance, imagine a robot equipped with a voice-controlled personal assistant. The user can speak commands
            or questions to the robot, and the speech recognition system within the personal assistant interprets the speech
            and converts it into text. This text is then processed, and the robot’s software can determine the appropriate
            action or response based on the user’s input.

            The speech recognition system analyses the audio input, taking into account factors such as pronunciation,
            accent, and context, to accurately transcribe the spoken words. Natural Language Processing (NLP) techniques
            are often employed to improve the accuracy and understanding of the input.
            Once the speech is transcribed into text, the robot can utilise this information to execute specific commands,
            perform tasks, or provide responses. For example, a user might say, “Robot, turn on the lights,” and the speech
            recognition system converts the spoken words into text, allowing the robot to understand the command and
            activate the corresponding light control mechanism.

            Speech recognition technology in robotics enhances human-robot interaction, making it more intuitive and user-
            friendly. It enables robots to understand spoken instructions, answer questions, or even engage in conversations
            with users. This technology finds applications in various domains, including home automation, customer service
            robots, voice-controlled robots, or assistive robots for individuals with disabilities.

            It’s  worth  noting  that  speech recognition  technology  is continuously  advancing,  and  different  systems may
            have varying levels of accuracy and language support. However, the goal remains the same: to enable robots to
            understand and respond to human speech, improving the overall user experience and interaction.





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