Coalescent Mobile Robotics robots help supermarkets by moving trolleys to help its staff. Specifically, our robots can move, dock trolleys, move docked trolleys and undock trolleys.
To be able to dock trolleys we need to have a very good estimate of the pose of the trolley with respect to the robot. This is necessary to approach the trolley and dock it without colliding with the trolley’s legs. Besides, we need to dock and move the trolley by keeping our robot in the center of the trolley. This allows the robot to move the trolley safely and predictably. Thus, we need to have a good estimate of the trolley pose with respect to the robot when the robot is docked to the trolley.
Using computer vision and laser sensory data, keep an accurate estimate of the relative pose of the trolley with respect to the robot. There might be multiple trolleys within the robot’s field of view. Thus, the solution should be reliable such that the robot can estimate its relative pose with respect to every trolley in a region of interest inside its field of view.
Our robots have multiple sensors that can aid in the detection of the trolleys:
Off of these sensors, the system shall estimate the relative pose of the trolleys within the robot’s field of view.
The following drawing illustrates an example of what we expect in terms of functionality. At the top-left corner, there is the robot with its pose in orange. There are two trolleys in its field of view (Trolley 1 and Trolley 2). For each trolley there is the correct (orange) pose as well as the predicted (green) one. In red you can see the translation error (on top of it, there will be an orientation error as well). In black you can see the position of the trolleys with respect to the robot.
Additionally, the solution might incorporate a standard deviation area of the different predictions. For instance, if the predictions follow a multinomial distribution, there could be more than one candidate solution. This can be important to analyze how the variance is reduced by incorporating new predictions, or how it increases in the presence of moving trolleys.
There will also be an acceptance criterion between the true and the estimated poses. For instance, that can be 1 cm position tolerance and 0.5 degrees orientation. The acceptance criteria shall have into account the mean, standard deviation, and maximum values of the error. These values shall be agreed with our robotics engineers to make sure the different tasks that the robot performs can be achieved with the agreed values.