How can LiDAR help robots avoid collisions with people?

LiDAR, or Light Detection and Ranging, works by emitting laser pulses and measuring the time it takes for them to reflect off objects in the environment. This data is used to create detailed 3D maps of surroundings, enabling robots to detect obstacles, including people, in real-time. By continuously scanning their surroundings with LiDAR, robots can identify potential collisions with people and adjust their trajectory to avoid accidents, ensuring safe interaction in shared spaces.

LiDAR technology assists robots in avoiding collisions with people by generating precise, real-time 3D maps of the surroundings. These maps enable robots to identify obstacles, including people, and adjust their path accordingly. By continuously analyzing LiDAR data, robots can predict potential collisions, adapt their navigation in response to dynamic environments, and maintain safe distances from individuals. Integrated with control systems, LiDAR ensures proactive collision avoidance, enhancing safety in human-populated settings without relying solely on visual data. This technology offers redundancy and reliability, complementing other sensors and providing robust collision avoidance capabilities even in challenging conditions.

LIDAR could help but n9 record of using LIDAR to avoid coolossion with humans , as a matter a fact we already solved that problem in two aspects , 1. Indilustrial robot have safety board as a standard (JIS) , SINCE 1970 or so that safety board ussese in every robot cell to clear the area of the robot from human , but also cam possibly easy maintain , 2. Cobots are new robot arm that obligate the specs in term of reducing the speed from 4500-5000 mm sec to 1200 mm sec , and reduce the payload , also other cations and sensors involved to insure safety working same area with human , for instance force control

In simple terms, LiDAR emits laser pulses that bounce off objects and return to the sensor. By measuring the time it takes for these pulses to return, LiDAR creates a 3D map of the environment. Thus, LiDAR-equipped robots can detect obstacles, including people, and navigate safely to avoid collisions.

Lidar is the ideal object detection sensor because it is an “active” sensor meaning it utilizes its own light source. Bouncing a laser off of an object is a really great way to see if it is there or not. Other techniques like camera which are “passive” suffer from lighting and contrast issues. Radar is good for detecting large, hard objects but has difficulty with resolution and detecting soft targets like people.

Even though Lidar is used in many use cases from robot navigation to human tracking, it has many challenges. (e.g) Lidar in a autonomous vacuum cleaner fails to detect table cloths. This can be avoided by using a camera in fusion with lidar.

In a busy place like a city street or mall, a robot with LiDAR sensors can avoid bumping into people. LiDAR works by sending out laser beams to create a map of its surroundings. If someone suddenly appears in its path, the LiDAR sees them and tells the robot to go a different way. So, the robot can move around safely without crashing into anyone. This helps make sure the robot doesn't hurt people while it's moving around in crowded places.

One of the main challenges with using Lidar is the Lidar processing software. Since the technology is so new, there are not many drivers, libraries and sample code to work off of. With more development and time, LiDAR and LiDAR software will be easier to use and implement.

In real life, a company uses LiDAR sensors in autonomous delivery robots to avoid collisions on sidewalks. They face challenges like false alarms from reflective surfaces and difficulty distinguishing between objects and people. To improve accuracy, they combine LiDAR with cameras and radar. Legal experts help establish guidelines for robot behavior in public spaces. This integrated approach enhances safety and reliability in crowded areas.

Advancements in LiDAR technology encompass increasing range and accuracy, mitigating environmental interference like weather or sunlight, and exploring novel applications like mapping and surveillance beyond collision avoidance. Balancing these factors drives ongoing development and adoption of LiDAR across robotics, autonomous vehicles, and diverse fields.