This paper presents a whole-body robot control method for exploring and probing a given region of interest. The ergodic control formalism behind such an exploration behavior consists of matching the time-averaged statistics of a robot trajectory with the spatial statistics of the target distribution. Most existing ergodic control approaches assume the robots/sensors as individual point agents moving in space. We introduce an approach exploiting multiple kinematically constrained agents on the whole-body of a robotic manipulator, where a consensus among the agents is found for generating control actions. To do so, we exploit an existing ergodic control formulation called heat equation-driven area coverage (HEDAC), combining local and global exploration on a potential field resulting from heat diffusion. Our approach extends HEDAC to applications where robots have multiple sensors on the whole-body (such as tactile skin) and use all sensors to optimally explore the given region. We show that our approach increases the exploration performance in terms of ergodicity and scales well to real-world problems using agents distributed on multiple robot links. We compare our method with HEDAC in kinematic simulation and demonstrate the applicability of an online exploration task with a 7-axis Franka Emika robot.