Abstract
This paper demonstrates an innovative group of robots, consisting of jumping rovers and a charging station, improved traversability and extended energy endurance when traveling to multiple target locations. By employing different jumping rovers with distinct energy consumption characteristics and jumping capabilities, we focus on searching for the most energy-efficient path of each jumping rover in a multi-waypoints visiting mission with obstacles. As jumping rovers can jump onto or over some obstacles without navigating around them, they have the potential to save energy by generating alternative paths to overcome obstacles. Moreover, due to the energy demands for the multi-waypoints mission and the limited battery capacity, a charging station is considered to provide extra energy for enhanced endurance during the mission. We first apply a refined rapidly-exploring random tree star (RRT∗) algorithm to find energy-efficient paths between any two target locations. Then, the genetic algorithm (GA) is applied to select the most profitable combination of paths to visit all targets with energy constraints. Finally, we verify the improved mobility and energy efficiency in both virtual simulation and experimental tests using a group of customized jumping rovers with a charging station and the proposed path planning and task allocation method.
Highlights
Unmanned ground vehicles (UGVs) have been used extensively for exploration in unknown or dangerous environments where humanity is not able to access
The objective for a team of UGVs is to visit a set of targets using the most energy-efficient route, where one stationary charging station is provided for the power supply
Constraint (14) specifies that the energy in the battery of each UGV is required to maintain above Emin,z for all the time, where xiS,zΔEi,z indicates that if UGV z gets charged after visiting target i, it will gain ΔEi,z to reach the initial energy amount, denoted as E0,z, and Vz (1, . . ., lz) represents the first lz elements in the set Vz
Summary
Unmanned ground vehicles (UGVs) have been used extensively for exploration in unknown or dangerous environments where humanity is not able to access. Considering the limitations of traditional UAVs and UGVs, we propose using a team of wheeled robots with jumping capabilities for multi-waypoints visiting missions with obstacles. Compared to our prior work in (Tan et al, 2020), the contribution of this paper includes the following points: (1) a new formulation of the multi-waypoints traveling mission of a robot team integrating the charging function and energy constraints. (2) a path planning algorithm with refined paths that consider more complicated geometries of an obstacle in both rolling and jumping motion, (3) introducing GA to determine both visiting and charging sequences, and (4) design and construction of a charging system that automatically docks with the jumping rovers.
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