Obstacle avoidance refers to the process by which a robot , through sensors , detects dynamic or static obstacles in its planned route, updates its path in real time according to a certain algorithm, avoids obstacles, and finally reaches its destination.
The first step for a robot to begin working is to quickly familiarize itself with its surroundings and understand its own location information. Currently, SLAMTEC's LiDAR sensors can help robots obtain high-precision contour information of their environment in real time, enabling the robot to perform functions such as autonomous localization, mapping, and obstacle avoidance.
Of course, relying solely on lidar sensors cannot achieve the desired effect. To address this, Slamtec has launched SLAMWARE, an autonomous positioning and navigation module that acts as the "cerebellum" of a robot and serves as a core hub for controlling the robot's movement.
For robots, the cerebellum can map the environment to guide their actions, but finding the optimal path from the starting point to the destination while avoiding obstacles is more difficult.
Slamtec's modular autonomous positioning and navigation system, SLAMWARE, incorporates LiDAR-based Simultaneous Localization and Mapping (SLAM) and path planning capabilities. It is also one of Slamtec's complete solutions for autonomous movement of service robots.
Compared to the open-source ROS robot operating system, SLAMWARE's built-in SLAM algorithm creates more accurate maps and maintains high positioning accuracy even under external interference. In practical applications, in addition to using SLAM to build environmental maps and achieve real-time localization, we also want the robot to automatically avoid obstacles in unknown environments and achieve autonomous movement. SLAMWARE uses the D* algorithm (i.e., dynamic heuristic pathfinding algorithm), which allows the robot to move freely in unfamiliar environments and avoid dynamic obstacles without pre-programmed maps.
Generally speaking, service robots work in complex environments, requiring not only the combination of "eyes" (LiDAR) and "cerebellum" but also the fusion of multiple sensors.
Meanwhile, SLAMWARE also supports multi-sensor fusion, including ultrasonic sensors, fall sensors, collision sensors, and depth cameras, which helps robots achieve more intelligent movement by fusing information from multiple sensors.
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